Tudóstér: Hajdu András publikációi

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feltöltött közlemény: 211 Open Access: 31
2024
  1. Lakatos, R., Bogacsovics, G., Harangi, B., Lakatos, I., Tiba, A., Tóth, J., Szabó, M., Hajdu, A.: A Machine Learning-Based Pipeline for the Extraction of Insights from Customer Reviews.
    Big Data Cogn. Comput. 8 (3), 1-24, 2024.
    Folyóirat-mutatók:
    Q2 Artificial Intelligence (2022)
    Q2 Computer Science Applications (2022)
    Q2 Information Systems (2022)
    Q2 Management Information Systems (2022)
  2. Lakatos, R., Pollner, P., Hajdu, A., Joó, T.: A multimodal deep learning architecture for smoking detection with a small data approach.
    Front. Artif. Intell. 7 1-8, 2024.
    Folyóirat-mutatók:
    Q2 Artificial Intelligence (2022)
2023
  1. Gombos, B., Nagy, Z., Hajdu, A., Nagy, J.: Climate change in the Debrecen area in the last 50 years and its impact on maize production.
    Idojaras. 127 (4), 485-504, 2023.
    Folyóirat-mutatók:
    Q4 Atmospheric Science (2022)
  2. Harangi, B., Baran, Á., Beregi-Kovács, M., Hajdu, A.: Composing Diverse Ensembles of Convolutional Neural Networks by Penalization.
    Mathematics. 11 (23), 1-19, 2023.
    Folyóirat-mutatók:
    Q2 Computer Science (miscellaneous) (2022)
    Q2 Engineering (miscellaneous) (2022)
    Q2 Mathematics (miscellaneous) (2022)
  3. Pándy, Á., Harangi, B., Hajdu, A.: Extracting Drug Names from Medical Reports.
    In: IEEE 18th International Conference on Computer Science and Information Technologies (CSIT), IEEE, Piscataway, 1-4, 2023. ISBN: 9798350360462
  4. Bogacsovics, G., Harangi, B., Hajdu, A.: Increasing the diversity of ensemble members for accurate brain tumor classification.
    In: 36th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2023, Institute of Electrical and Electronics Engineers Inc., [s.l.], 529-534, 2023. ISBN: 9798350312249
  5. Liu, Y., Zhou, S., Wang, L., Xu, M., Huang, X., Li, Z., Hajdu, A., Zhang, L.: Machine learning approach combined with causal relationship inferring unlocks the shared pathomechanism between COVID-19 and acute myocardial infarction.
    Front. Microbiol. 14 1-10, 2023.
    Folyóirat-mutatók:
    Q1 Microbiology (2022)
    Q1 Microbiology (medical) (2022)
  6. Pándy, Á., Kovács, L., Kovács, Á., Hajdu, A.: Steering Angle Prediction From a Camera Image as a Backup Service.
    IEEE Sens. Lett. 7 (11), 1-4, 2023.
    Folyóirat-mutatók:
    Q2 Electrical and Electronic Engineering (2022)
    Q2 Instrumentation (2022)
  7. Tóth, J., Tomán, H., Hajdu, G., Hajdu, A.: Using Noisy Evaluation to Accelerate Parameter Optimization of Medical Image Segmentation Ensembles.
    Mathematics. 11 (18), 1-17, 2023.
    Folyóirat-mutatók:
    Q2 Computer Science (miscellaneous) (2022)
    Q2 Engineering (miscellaneous) (2022)
    Q2 Mathematics (miscellaneous) (2022)
2022
  1. Zhou, S., Szöllősi, A., Huang, X., Chang Chien, Y., Hajdu, A.: A Novel Immune-Related Gene Prognostic Index (IRGPI) in Pancreatic Adenocarcinoma (PAAD) and Its Implications in the Tumor Microenvironment.
    Cancers (Basel). 14 (22), 1-25, 2022.
    Folyóirat-mutatók:
    Q2 Cancer Research
    Q1 Oncology
  2. Kapusi, T., Erdei, T., Husi, G., Hajdu, A.: Application of Deep Learning in the Deployment of an Industrial SCARA Machine for Real-Time Object Detection.
    Robotics. 11 (4), 1-20, 2022.
    Folyóirat-mutatók:
    Q2 Artificial Intelligence
    Q1 Control and Optimization
    Q1 Mechanical Engineering
  3. Hajdu, A., Terdik, G., Tiba, A., Tomán, H.: A stochastic approach to handle resource constraints as knapsack problems in ensemble pruning.
    Mach. Learn. 111 1551-1595, 2022.
    Folyóirat-mutatók:
    Q1 Artificial Intelligence
    Q1 Software
  4. Huang, X., Zhou, S., Tóth, J., Hajdu, A.: Cuproptosis-related gene index: a predictor for pancreatic cancer prognosis, immunotherapy efficacy, and chemosensitivity.
    Front. Immunol. 13 1-31, 2022.
    Folyóirat-mutatók:
    Q1 Immunology
    Q1 Immunology and Allergy
  5. Kapusi, T., Kovács, L., Hajdu, A.: Deep learning-based anomaly detection for imaging in autonomous vehicles.
    In: 2022 IEEE 2nd Conference on Information Technology and Data Science (CITDS): Proceedings (2022.05.16-18.)(Debrecen). Szerk.: Fazekas István, IEEE, Piscataway (NJ), 142-147, 2022. ISBN: 9781665496520
  6. Bogacsovics, G., Tóth, J., Hajdu, A., Harangi, B.: Enhancing CNNs through the use of hand-crafted features in automated fundus image classification.
    Biomed. Signal Process. Control. 76 1-10, 2022.
    Folyóirat-mutatók:
    Q1 Biomedical Engineering
    Q1 Health Informatics
    Q1 Signal Processing
  7. Pándy, Á., Kun, D., Kovács, L., Vasváry, G., Pánti, Z., Hajdu, A.: Image sensor based steering signal for a digital actuator system.
    In: 2022 IEEE 2nd Conference on Information Technology and Data Science (CITDS) / Fazekas István, IEEE, Piscataway, 229-234, 2022. ISBN: 9781665496537
  8. Lakatos, R., Bogacsovics, G., Hajdu, A.: Predicting the direction of the oil price trend using sentiment analysis.
    In: IEEE 2nd Conference on Information Technology and Data Science (CITDS) : Proceedings. Ed.: Fazekas István, Institute of Electrical and Electronics Engineers (IEEE), Piscataway, 177-182, 2022.
2021
  1. Bogacsovics, G., Hajdu, A., Harangi, B., Lakatos, I., Lakatos, R., Szabó, M., Tiba, A., Tóth, J., Tarcsi, Á.: Adatelemzési folyamat és keretrendszer a közigazgatás számára.
    Közigazgatástudomány. 1 (2), 146-158, 2021.
  2. Bogacsovics, G., Hajdu, A., Harangi, B.: Cell Segmentation in Digitized Pap Smear Images Using an Ensemble of Fully Convolutional Networks.
    In: 2021 IEEE Signal Processing in Medicine and Biology Symposium : Proceedings, IEEE, Philadelphia, 1-6, 2021. ISBN: 9781665428972
  3. Lantang, O., Terdik, G., Hajdu, A., Tiba, A.: Comparison of single and ensemble-based convolutional neural networks for cancerous image classification.
    Ann. Math. Inform. 54 45-56, 2021.
    Folyóirat-mutatók:
    Q3 Computer Science (miscellaneous)
    Q4 Mathematics (miscellaneous)
  4. Ahammed, A., Harangi, B., Hajdu, A.: Hybrid AdaBoost and Naïve Bayes classifier for supervised learning.
    In: Proceedings of the 1st Conference on Information Technology and Data Science. Ed.: István Fazekas, András Hajdu, Tibor Tómács, CEUR Workshop Proceedings, Debrecen, 1-18, 2021, (CEUR Workshop Proceedings, ISSN 1613-0073 ; 2874.)
  5. Lantang, O., Terdik, G., Hajdu, A., Tiba, A.: Investigation of the efficiency of an interconnected convolutional neural network by classifying medical images.
    Ann. Math. Inform. 53 219-234, 2021.
    Folyóirat-mutatók:
    Q3 Computer Science (miscellaneous)
    Q4 Mathematics (miscellaneous)
  6. Bankó, C., Nagy, Z., Nagy, M., Szemán-Nagy, G., Rebenku, I., Imre, L., Tiba, A., Hajdu, A., Szöllősi, J., Kéki, S., Bacsó, Z.: Isocyanide Substitution in Acridine Orange Shifts DNA Damage-Mediated Phototoxicity to Permeabilization of the Lysosomal Membrane in Cancer Cells.
    Cancers (Basel). 13 (22), 1-24, 2021.
    Folyóirat-mutatók:
    Q2 Cancer Research
    Q1 Oncology
  7. Lakatos, I., Hajdu, A., Harangi, B.: Molecule Classification Using Visualization and Convolutional Neural Network.
    In: IEEE 18th International Symposium on Biomedical Imaging (ISBI), IEEE, Piscataway, 1695-1698, 2021.
  8. Bogacsovics, G., Hajdu, A., Harangi, B., Lakatos, I., Lakatos, R., Szabó, M., Tiba, A., Tóth, J.: Napelemfarmok Magyarország területén történő elhelyezését segítő döntéstámogató rendszer fejlesztése.
    Közigazgatástudomány. 1 (2), 134-145, 2021.
  9. Kolozsvári, L., Bérczes, T., Hajdu, A., Gesztelyi, R., Tiba, A., Varga, I., Al-Tammemi, A., Szőllősi, G., Kolozsváriné Harsányi, S., Garbóczy, S., Zsuga, J.: Predicting the epidemic curve of the coronavirus (SARS-CoV-2) disease (COVID-19) using artificial intelligence: an application on the first and second waves.
    Informatics in Medicine Unlocked. 25 1-13, 2021.
    Folyóirat-mutatók:
    Q2 Health Informatics
  10. Bogacsovics, G., Hajdu, A., Lakatos, R., Beregi-Kovács, M., Tiba, A., Tomán, H.: Replacing the SIR epidemic model with a neural network and training it further to increase prediction accuracy.
    Ann. Math. Inform. 53 73-91, 2021.
    Folyóirat-mutatók:
    Q3 Computer Science (miscellaneous)
    Q4 Mathematics (miscellaneous)
2020
  1. Harangi, B., Baran, Á., Hajdu, A.: Assisted deep learning framework for multi-class skin lesion classification considering a binary classification support.
    Biomed. Signal Process. Control. 62 1-7, 2020.
    Folyóirat-mutatók:
    Q2 Health Informatics
    Q2 Signal Processing
  2. Beregi-Kovács, M., Baran, Á., Hajdu, A.: Efficient Learning of Model Weights via Changing Features During Training.
    2020 IEEE 24th International Conference on Intelligent Engineering Systems (INES) 2020 43-48, 2020.
  3. Tóth, J., Tomán, H., Hajdu, A.: Efficient sampling-based energy function evaluation for ensemble optimization using simulated annealing.
    Pattern Recognit. 107 1-12, 2020.
    Folyóirat-mutatók:
    D1 Artificial Intelligence
    D1 Computer Vision and Pattern Recognition
    D1 Signal Processing
    D1 Software
  4. Porwal, P., Pachade, S., Kokare, M., Deshmukh, G., Son, J., Bae, W., Liu, L., Wang, J., Liu, X., Gao, L., Wu, T., Xiao, J., Wang, F., Yin, B., Wang, Y., Danala, G., He, L., Choi, Y., Lee, Y., Jung, S., Li, Z., Sui, X., Wu, J., Li, X., Zhou, T., Tóth, J., Baran, Á., Kori, A., Chennamsetty, S., Safwan, M., Alex, V., Lyu, X., Cheng, L., Chu, Q., Li, P., Ji, X., Zhang, S., Shen, Y., Dai, L., Saha, O., Sathish, R., Melo, T., Araújo, T., Harangi, B., Sheng, B., Fang, R., Sheet, D., Hajdu, A., Zheng, Y., Mendonça, A., Zhang, S., Campilho, A., Zheng, B., Shen, D., Giancardo, L., Quellec, G., Mériaudeau, F.: IDRiD: Diabetic Retinopathy: segmentation and grading challenge.
    Med. Image Anal. 59 1-26, 2020.
    Folyóirat-mutatók:
    D1 Computer Graphics and Computer-Aided Design
    D1 Computer Vision and Pattern Recognition
    D1 Health Informatics
    D1 Radiological and Ultrasound Technology
    D1 Radiology, Nuclear Medicine and Imaging
2019
  1. Tóth, J., Kapusi, T., Harangi, B., Tomán, H., Hajdu, A.: Accelerating the Optimization of a Segmentation Ensemble using Image Pyramids.
    In: 11th International Symposium on Image and Signal Processing and Analysis (ISPA 2019). Eds.: S. Lončarić, R. Bregović, M. Carli, M. Subašić, Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ, USA, 43-48, 2019. ISBN: 9781728131405
  2. Harangi, B., Tóth, J., Baran, Á., Hajdu, A.: Automatic screening of fundus images using a combination of convolutional neural network and hand-crafted features.
    In: 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). Ed.: Riccardo Barbieri, Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ, USA, 2699-2702, 2019. ISBN: 9781538613122
  3. Harangi, B., Tóth, J., Bogacsovics, G., Kupás, D., Kovács, L., Hajdu, A.: Cell detection on digitized Pap smear images using ensemble of conventional image processing and deep learning techniques.
    In: 11th International Symposium on Image and Signal Processing and Analysis (ISPA 2019). Eds.: S. Lončarić, R. Bregović, M. Carli, M. Subašić, Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ, USA, 38-42, 2019. ISBN: 9781728131405
  4. Lantang, O., Tiba, A., Hajdu, A., Terdik, G.: Convolutional Neural Network For Predicting The Spread of Cancer.
    In: Proceedings of the 10th IEEE International Conference on Cognitive Infocommunications : CogInfoCom 2019. Szerk.: Péter Baranyi, IEEE-Inst Electrical Electronics Engineers Inc, Piscataway, 175-180, 2019. ISBN: 9781728147932
  5. Tiba, A., Bartik, Z., Tomán, H., Hajdu, A.: Detecting outlier and poor quality medical images with an ensemble-based deep learning system.
    In: 11th International Symposium on Image and Signal Processing and Analysis (ISPA), Ieee-Inst Electrical Electronics Engineers Inc, Piscataway, 99-104, 2019. ISBN: 9781728131405
  6. Hajdu, L., Harangi, B., Tiba, A., Hajdu, A.: Detecting Periodicity in Digital Images by the LLL Algorithm.
    In: Progress in Industrial Mathematics at ECMI 2018. Ed.: István Faragó, Ferenc Izsák, Péter L. Simon, Springer, Cham, 613-619, 2019, ( Mathematics in Industry ; 30.)( The European Consortium for Mathematics in Industry ; 30.) ISBN: 9783030275495
  7. Tóth, J., Tornai, R., Labancz, I., Hajdu, A.: Efficient Visualization for an Ensemble-based System.
    Acta Polytech. Hung. 16 (2), 59-75, 2019.
    Folyóirat-mutatók:
    Q2 Engineering (miscellaneous)
    Q2 Multidisciplinary
  8. Hajdu, A., Tijdeman, R., Hajdu, L.: Finding well approximating lattices for a finite set of points.
    Math. Comput. 88 (315), 369-387, 2019.
    Folyóirat-mutatók:
    D1 Algebra and Number Theory
    D1 Applied Mathematics
    D1 Computational Mathematics
  9. Tiba, A., Hajdu, A., Terdik, G., Tomán, H.: Optimizing Majority Voting Based Systems Under a Resource Constraint for Multiclass Problems.
    In: Progress in Industrial Mathematics at ECMI 2018. Ed.: István Faragó, Ferenc Izsák, Péter L. Simon, Springer, Cham, 529-534, 2019, (Mathematics in Industry ; 30.)(The European Consortium for Mathematics in Industry ; 30.) ISBN: 9783030275495
  10. Kupás, D., Török, P., Hajdu, A., Harangi, B.: Visualization of Fibroid in Laparoscopy Videos using Ultrasound Image Segmentation and Augmented Reality.
    In: Proceedings of the 11th International Symposium on Image and Signal Processing and Analysis. Eds.: Lončarić S., Bregović R., Carli M., Subašić M, University of Zagreb, Dubrovnik, 60-63, 2019. ISBN: 9781728131405
2018
  1. Harangi, B., Baran, Á., Hajdu, A.: Classification of skin lesions using an ensemble of deep neural networks.
    In: 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) / Gregg Suaning, Olaf Dossel, IEEE, Hawaii, USA, 2575-2578, 2018. ISBN: 9781538636466
  2. Hajdu, A., Harangi, B., Tóth, J., Pap, M., Baran, Á.: Combining Convolutional Neural Networks and Hand-Crafted Features in Medical Image Classification Tasks.
    In: 20th European Conference on Mathematics for Industry : Book of Abstracts. Ed.: Bodó Á., Fekete I., Izsák F., Maros G., Simon L. P, Bolyai János Matematikai Társulat, Budapest, 299, 2018.
  3. Antal, B., Tavares, M., Kovács, L., Harangi, B., Lázár, I., Nagy, B., Kovács, G., Szakács, J., Tóth, J., Pető, T., Csutak, A., Hajdu, A.: Data analysis applied to diabetic retinopathy screening: performance evaluation.
    Ann. Math. Inform. 49 3-9, 2018.
    Folyóirat-mutatók:
    Q3 Computer Science (miscellaneous)
    Q4 Mathematics (miscellaneous)
  4. Harangi, B., Tóth, J., Hajdu, A.: Fusion of deep convolutional neural networks for microaneurysm detection in color fundus images.
    In: 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) / Gregg Suaning, Olaf Dossel, IEEE, Hawaii, USA, 3705-3708, 2018. ISBN: 9781538636466
  5. Kovács, L., Kovács, R., Hajdu, A.: High Performance Computing in Medical Image Analysis HuSSaR.
  6. Kovács, L., Hajdu, A., Harangi, B., Sós, A.: Hybrid Small Size hpcResource - HuSSaR [mintaotalom].
    [szabadalom]
  7. Burai, P., Hajdu, A., Felipe, -., Harangi, B.: Segmentation of the uterine wall by an ensemble of fully convolutional neural networks.
    In: 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) / Gregg Suaning, Olaf Dossel, IEEE, Hawaii, USA, 49-52, 2018. ISBN: 9781538636466
2017
  1. Pap, M., Harangi, B., Hajdu, A.: Automatic Pigment Network Classification Using a Combination of Classical Texture Descriptors and CNN Features.
    In: Proceedings 2017 IEEE 30th International Symposium on Computer-Based Medical Systems CBMS 2017 / Panagiotis D. Bamidis, Stathis Th. Konstantinidis, Pedro Pereira Rodrigues, IEEE, Piscataway, 343-348, 2017, (ISSN 2372-9198) ISBN: 9781538617106
  2. Antal, B., Tavares, M., Kovács, L., Harangi, B., Pető, T., Csutak, A., Hajdu, A.: Data Analysis Applied to Diabetic Retinopathy Screening: Performance Evaluation.
    Eur. J. Ophthalmol. 27 (3), E124-E125, 2017.
  3. Harangi, B., Hajdu, A., Lampé, R., Török, P.: Differentiating ureter and arteries in the pelvic via endoscope using deep neural network.
    In: ISPA 2017 10th International Symposium on Image and Signal Processing and Analysis. Eds.: Stanislav Kovacic, Sven Loncaric, Matej Kristan, Vitomir Struc, Mladen Vucic, University of Zagreb, Zagreb, 86-89, 2017. ISBN: 9781509040117
  4. Tiba, A., Harangi, B., Hajdu, A.: Efficient Texture Regularity Estimation for Second Order Statistical Descriptors.
    In: Proceedings of the 10th International Image and Signal Processing and Analysis (ISPA). Ed.: Stanislav Kovačič, Sven Lončarić, Matej Kristan, Vitomir Štruc, Mladen Vučić, University of Zagreb, Zagreb, 90-94, 2017. ISBN: 9781509040117
  5. Hajdu, A., Harangi, B., Besenczi, R., Lázár, I., Emri, G., Hajdu, L., Tijdeman, R.: Measuring regularity of network patterns by grid approximations using the LLL algorithm.
    In: Proceedings of the 23rd International Conference on Pattern Recognition (ICPR 2016), Cancun, Mexico, 2016, IEEE, [Piscataway], 1524-1529, 2017. ISBN: 9781509048472
2016
  1. Azodinia, M., Hajdu, A.: A novel combinational relevance feedback based method for content-based image retrieval.
    Acta Polytech. Hung. 13 (5), 121-134, 2016.
    Folyóirat-mutatók:
    Q2 Engineering (miscellaneous)
    Q2 Multidisciplinary
  2. Azodinia, M., Hajdu, A.: A novel method to increase the performance of recommender systems using a parallel CBIR approach.
    IJCSIS. 14 (10), 205-213, 2016.
  3. Besenczi, R., Tóth, J., Hajdu, A.: A review on automatic analysis techniques for color fundus photographs.
    Comput. Struct. Biotechnol. J. 14 371-384, 2016.
    Folyóirat-mutatók:
    Q2 Biochemistry
    Q1 Biophysics
    Q1 Biotechnology
    Q1 Computer Science Applications
    Q2 Genetics
    Q2 Structural Biology
  4. Kovács, G., Hajdu, A.: A self-calibrating approach for the segmentation of retinal vessels by template matching and contour reconstruction.
    Med. Image Anal. 29 24-46, 2016.
    Folyóirat-mutatók:
    D1 Computer Graphics and Computer-Aided Design
    D1 Computer Vision and Pattern Recognition
    D1 Health Informatics
    D1 Radiological and Ultrasound Technology
    D1 Radiology, Nuclear Medicine and Imaging
  5. Hajdu, A., Tomán, H., Kovács, L., Hajdu, L.: Composing ensembles by stochastic approach under execution time constraint.
    In: Proceedings of the 23rd International Conference on Pattern Recognition (ICPR 2016), Cancun, Mexico, 2016, IEEE, [Piscataway], 222-227, 2016.
  6. Karimi, R., Hajdu, A.: HTSFinder: Powerful pipeline of DNA signature discovery by parallel and distributed computing.
    Evol. Bioinform. 12 73-85, 2016.
    Folyóirat-mutatók:
    Q2 Computer Science Applications
    Q2 Ecology, Evolution, Behavior and Systematics
    Q3 Genetics
2015
  1. Azodinia, M., Hajdu, A.: A method for image retrieval using combination of color and frequency layers.
    IJCA. 118 (3), 10-13, 2015.
  2. Tóth, J., Bartha, L., Szabó, T., Lázár, I., Harangi, B., Hajdu, A.: An online application for storing, analyzing, and sharing dermatological data.
    In: 6th IEEE Conference on Cognitive Infocommunications CogInfoCom 2015 : Proceedings, October 19-21, 2015, Széchenyi István University Győr, Hungary, IEEE, Danvers, 339-342, 2015. ISBN: 9781467381284
  3. Azodinia, M., Hajdu, A.: A recommender system that deals with items having an image as well as quantitative features.
    In: Proceedings of the 9th International Symposium on Intelligent Signal Processing (WISP), 2015 May 15-17, Siena, IEEE, [Piscataway], 1-6, 2015. ISBN: 9781479972524
  4. Besenczi, R., Szitha, K., Harangi, B., Csutak, A., Hajdu, A.: Automatic optic disc and optic cup detection in retinal images acquired by mobile phone.
    In: ISPA 2015 : 9th International Symposium on Image and Signal Processing and Analysis. Eds.: S. Loncaric, D. Lerski, H. Eskola, R. Bregovic, University of Zagreb, Zagreb, 193-198, 2015, (ISSN 1845-5921) ISBN: 9781467380324
  5. Török, Z., Pető, T., Csősz, É., Tukacs, E., Molnár, Á., Berta, A., Tőzsér, J., Hajdu, A., Nagy, V., Domokos, B., Csutak, A.: Combined Methods for Diabetic Retinopathy Screening, Using Retina Photographs and Tear Fluid Proteomics Biomarkers.
    J. Diabetes Res. 2015 1-8, 2015.
    Folyóirat-mutatók:
    Q2 Endocrinology
    Q2 Endocrinology, Diabetes and Metabolism
  6. Azodinia, M., Farrokhi, V., Hajdu, A.: Constant time median filtering of extra large images using Hadoop.
    In: Proceedings of the 9th International Conference on Applied Informatics January 29 - Februar 1, 2014. Eger, Hungary Volume I [elektronikus dokumentum]. Ed.: by Kovács Emőd, Kusper Gábor, Kunkli Roland, Tómács Tibor, Eszterházy Károly Főiskola, Eger, 93-101, 2015. ISBN: 9786155297182
  7. Harangi, B., Hajdu, A.: Detection of the optic disc in fundus images by combining probability models.
    Comput. Biol. Med. 65 10-24, 2015.
    Folyóirat-mutatók:
    Q2 Computer Science Applications
    Q2 Health Informatics
  8. Tóth, J., Tomán, H., Hajdu, A.: Improving the Performance of an Ensemble-Based Exudate Detection System using Stochastic Parameter Optimization.
    In: 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). Eds.: Sergio Cerutti, Paolo Bonato, Institute of Electrical and Electronics Engineers (IEEE), Seattle (WA), USA, 5243-5246, 2015.
  9. Fazekas, Z., Hajdu, A., Lázár, I., Kovács, G., Csákány, B., Calugaru, D., Shah, R., Adam, E., Talu, S.: Influence of using different segmentation methods on the fractal properties of the identified retinal vascular networks in healthy retinas and retinas with Vein occlusion.
    In: Képfeldolgozók és Alakfelismerők Társaságának 10. országos konferenciája, [s.n.], [Kecskemét], 361-373, 2015.
  10. Lázár, I., Hajdu, A.: Segmentation of retinal vessels by means of directional response vector similarity and region growing.
    Comput. Biol. Med. 66 209-221, 2015.
    Folyóirat-mutatók:
    Q2 Computer Science Applications
    Q2 Health Informatics
  11. Karimi, R., Hajdu, A.: SRIdent: a novel pipeline for real-time identification of species from high-throughput sequencing reads in metagenomics and clinical diagnostic assays.
    In: 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Milan, 2015. Proceedings, IEEE, [Piscataway], 6481-6484, 2015.
2014
  1. Besenczi, R., Szitha, K., Hajdu, A.: A framework for distributed processing on an offline cell phone network.
    In: 5th IEEE International Conference on Cognitive Infocommunications CogInfoCom 2014 : Proceedings, Vietri sul Mare, Italy. Ed.: Péter Baranyi, IEEE, Danvers, 257-262, 2014. ISBN: 9781479972807
  2. Antal, B., Hajdu, A.: An ensemble-based system for automatic screening of diabetic retinopathy.
    Knowledge-Based Syst. 60 20-27, 2014.
    Folyóirat-mutatók:
    Q1 Artificial Intelligence
    Q1 Information Systems and Management
    D1 Management Information Systems
    D1 Software
  3. Tóth, J., Kovács, L., Harangi, B., Kiss, C., Mohácsi, A., Orosz, Z., Hajdu, A.: An Online Benchmark System for Image Processing Algorithms.
    In: 5th IEEE International Conference on Cognitive Infocommunications. Ed.: Baranyi Péter, CogInfoCom, Vietri sul Mare, Italy, 377-385, 2014. ISBN: 9781479972807
  4. Tóth, J., Kovács, L., Harangi, B., Kiss, C., Mohácsi, A., Orosz, Z., Hajdu, A.: An Online System for Algorithm Benchmarking.
    In: 5th IEEE International Conference on Cognitive Infocommunications. Ed.: Baranyi Péter, CogInfoCom, Vietri sul Mare, Italy, 383, 2014. ISBN: 9781479972807
  5. Harangi, B., Hajdu, A.: Automatic exudate detection by fusing multiple active contours and regionwise classification.
    Comput. Biol. Med. 54 156-171, 2014.
    Folyóirat-mutatók:
    Q2 Computer Science Applications
    Q3 Health Informatics
  6. Karimi, R., Bellatreche, L., Girard, P., Boukorca, A., Hajdu, A.: BINOS4DNA: Bitmap indexes and NoSQL for identifying species with DNA signatures through metagenomics samples.
    In: Information Technology in Bio- and Medical Informatics : 5th International Conference, ITBAM 2014, Munich, Germany, September 2, 2014. Proceedings. Ed.: Miroslav Bursa, Sami Khuri, M. Elena Renda, Springer International Publishing, Cham, 1-14, 2014, (Lecture Notes in Computer Science, ISSN 0302-9743 ; 8649) ISBN: 9783319102658
  7. Harangi, B., Hajdu, A.: Detection of Exudates in Fundus Images Using a Markovian Segmentation Model.
    Conf Proc IEEE Eng Med Biol Soc. 36 130-133, 2014.
  8. Besenczi, R., Szitha, K., Hajdu, A.: Distributed eye lesion detection on an offline cell phone network.
    In: 5th IEEE International Conference on Cognitive Infocommunications CogInfoCom 2014 : Proceedings, Vietri sul Mare, Italy. Ed.: Péter Baranyi, IEEE, Danvers, 467, 2014. ISBN: 9781479972807
  9. Tóth, J., Szakács, L., Hajdu, A.: Finding the optimal parameter setting for an ensemble-based lesion detector.
    Proc. Int. Conf. Image Proc. 3532-3536, 2014.
2013
  1. Lámfalusi, C., Girus, D., Kruppa, K., Tóth, J., Hajduné Pocsai, E., Kunkli, R., Hajdu, A., Bálint, B.: Adding a scalable visualization technique to the UCSC genome browser.
    In: 4th IEEE International Conference on Cognitive Infocommunications CogInfoCom 2013 : Proceedings, December 2-5, 2013 Budapest, Hungary. Ed.: Péter Baranyi, IEEE, Danvers, 943-944, 2013. ISBN: 9781479915439
  2. Harangi, B., Hajdu, A.: Aktív kontúr használatával és régió alapú osztályozással pontosított exudátum detektáló algoritmus.
    In: Képfeldolgozók és Alakfelismerők országos 9. konferenciája : KÉPAF Konferencia kiadvány. Szerk.: Czúni László, Képfeldolgozók és Alakfelismerők Társasága, Bakonybél, 379-392, 2013.
  3. Antal, B., Lázár, I., Hajdu, A.: An adaptive weighting approach for ensemble-based detection of microaneurysms in color fundus images.
    In: Képfeldolgozók és Alakfelismerők országos 9. konferenciája : KÉPAF Konferencia kiadvány. Szerk.: Czúni László, NJSZT-KÉPAF, Bakonybél, 393-403, 2013.
  4. Antal, B., Remenyik, B., Hajdu, A.: An Unsupervised Ensemble-based Markov Random Field Approach to Microscope Cell Image Segmentation.
    In: 10th International Conference on Signal Processing and Multimedia Applications. Ed.: Mohammad S. Obaidat, SciTePress, Reykjavik, Izland, 94-99, 2013.
  5. Ayoub, A., Hajdu, A., Nagy, Á., Szakács, J., Tóth, J.: Automatikus pigmenthálózat-detektálás dermatoszkópos képeken.
    In: Képfeldolgozók és Alakfelismerők 9. országos konferenciája. Szerk.: Czúni László, NJSZT-KÉPAF, Bakonybél, 439-449, 2013.
  6. Tóth, J., Papp, I., Tornai, R., Labancz, I., Hajduné Pocsai, E., Hajdu, A.: Cognitive visualization for the design of complex systems.
    In: 4th IEEE International Conference on Cognitive Infocommunications CogInfoCom 2013 : Proceedings, December 2-5, 2013 Budapest, Hungary. Ed.: Péter Baranyi, IEEE, Danvers, 419-422, 2013. ISBN: 9781479915439
  7. Hajdu, A., Hajdu, L., Kovács, L., Tomán, H.: Diversity measures for majority voting in the spatial domain.
    In: Hybrid Artificial Intelligent Systems : 8th International Conference, HAIS 2013, Salamanca, Spain, September 11-13, 2013. Proceedings, Springer-Verlag, Berlin Heidelberg, 314-323, 2013, (Lecture Notes in Artificial Intelligence, ISSN 0302-9743 ; 8073) ISBN: 9783642408458
  8. Lámfalusi, C., Girus, D., Kruppa, K., Tóth, J., Hajduné Pocsai, E., Kunkli, R., Hajdu, A., Bálint, B.: Extending the visualization capabilities of a genome browser.
    In: 4th IEEE International Conference on Cognitive Infocommunications CogInfoCom 2013 : Proceedings, December 2-5, 2013 Budapest, Hungary. Ed.: Péter Baranyi, IEEE, Danvers, 419-422, 2013. ISBN: 97814799115439
  9. Hajdu, A., Hajdu, L., Jónás, Á., Kovács, L., Tomán, H.: Generalizing the majority voting scheme to spatially constrained voting.
    IEEE Trans. Image Process. 22 (11), 4182-4194, 2013.
    Folyóirat-mutatók:
    D1 Computer Graphics and Computer-Aided Design
    D1 Software
  10. Harangi, B., Hajdu, A.: Improving automatic exudate detection based on the fusion of the results of multiple active contours.
    Proc. IEEE Int. Symp. Biomed. Imaging. 1 45-48, 2013.
  11. Antal, B., Hajdu, A.: Improving microaneurysm detection in color fundus images by using context-aware approaches.
    Comput. Med. Imaging Graph. 37 (5), 403-408, 2013.
    Folyóirat-mutatók:
    Q1 Computer Graphics and Computer-Aided Design
    Q2 Computer Vision and Pattern Recognition
    Q2 Health Informatics
    Q2 Radiological and Ultrasound Technology
    Q2 Radiology, Nuclear Medicine and Imaging
  12. Lázár, I., Hajdu, A.: Keresztmetszeti intenzitás profilokon alapuló mikroaneurizma detektálás és érhálózat szegmentálás retina képeken.
    In: Képfeldolgozók és Alakfelismerők 9. konferenciája. Szerk.: Czúni László, NJSZT-KÉPAF, Bakonybél, 404-412, 2013.
  13. Lázár, I., Hajdu, A.: Retinal Microaneurysm Detection Through Local Rotating Cross-Section Profile Analysis.
    IEEE Trans. Med. Imaging. 32 (2), 400-407, 2013.
    Folyóirat-mutatók:
    D1 Computer Science Applications
    D1 Electrical and Electronic Engineering
    D1 Radiological and Ultrasound Technology
    D1 Software
  14. Török, Z., Pető, T., Csősz, É., Tukacs, E., Molnár, Á., Maros-Szabó, Z., Berta, A., Tőzsér, J., Hajdu, A., Nagy, V., Domokos, B., Csutak, A.: Tear fluid proteomics multimarkers for diabetic retinopathy screening.
    BMC Ophthalmol. 13 (1), 1-8, 2013.
    Folyóirat-mutatók:
    Q2 Medicine (miscellaneous)
    Q2 Ophthalmology
  15. Kovács, G., Hajdu, A.: Translation invariance in the polynomial kernel space and its applications in kNN classification.
    Neural Process. Lett. 37 (2), 207-233, 2013.
    Folyóirat-mutatók:
    Q3 Artificial Intelligence
    Q2 Computer Networks and Communications
    Q3 Neuroscience (miscellaneous)
    Q2 Software
2012
  1. Antal, B., Lázár, I., Hajdu, A.: An adaptive weighting approach for ensemble-based detection of microaneurysms in color fundus images.
    Conf Proc IEEE Eng Med Biol Soc. 5955-5958, 2012.
  2. Antal, B., Lázár, I., Hajdu, A.: An Ensemble Approach to Improve Microaneurysm Candidate Extraction.
    In: e-Business and Telecommunications : 7th International Joint Conference, ICETE, Athens, Greece, July 26-28, 2010 : Revised Selected Papers. Eds.: Mohammad S. Obaidat, George A. Tsihrintzis, Joaquim Filipe, Springer Verlag, Heidelberg, 378-394, 2012, (Communications in Computer and Information Science, 1865-0929 ; Vol. 222.) ISBN: 9783642252051
  3. Hajdu, A., Tóth, J., Pistár, Z., Domokos, B., Török, Z.: An ensemble-based collaborative framework to support customized user needs.
    In: 3rd IEEE International Conference on Cognitive Infocommunications, CogInfoCom 2012 : Proceedings, December 2-5, 2012 Košice, Slovakia. Ed.: Péter Baranyi, IEEE, Danvers, 285-290, 2012. ISBN: 9781467351874
  4. Antal, B., Hajdu, A.: An Ensemble-Based System for Microaneurysm Detection and Diabetic Retinopathy Grading.
    IEEE Trans. Biomed. Eng. 59 (6), 1720-1726, 2012.
    Folyóirat-mutatók:
    Q2 Biomedical Engineering
  5. Hajdu, A., Hajdu, L., Tijdeman, R.: Approximation of the Euclidean Distance by Chamfer Distances.
    Acta Cybern. 20 (3), 399-417, 2012.
    Folyóirat-mutatók:
    Q4 Computational Theory and Mathematics
    Q3 Computer Science (miscellaneous)
    Q4 Computer Vision and Pattern Recognition
    Q3 Electrical and Electronic Engineering
    Q3 Information Systems and Management
    Q4 Management Science and Operations Research
    Q4 Software
    Q4 Theoretical Computer Science
  6. Antal, B., Hajdu, A., Maros-Szabó, Z., Török, Z., Csutak, A., Pető, T.: A two-phase decision support framework for the automatic screening of digital fundus images.
    J. Comput. Sci. 3 (5), 262-268, 2012.
    Folyóirat-mutatók:
    Q1 Computer Science (miscellaneous)
    Q2 Modeling and Simulation
    Q2 Theoretical Computer Science
  7. Ayoub, A., Hajdu, A., Nagy, Á.: Automatic Detection of Pigmented Network in Melanoma Dermoscopic Images.
    IJCSNS. 2 58-63, 2012.
  8. Harangi, B., Hajdu, A., Lázár, I.: Automatic Exudate Detection Using Active Contour Model and Regionwise Classification.
    Conf Proc IEEE Eng Med Biol Soc. 1 5951-5954, 2012.
  9. Harangi, B., Antal, B., Hajdu, A.: Automatic exudate detection with improved Naïve-Bayes classifier.
    In: Proceedings of the 25th IEEE International Symposium on Computer-Based Medical System [elektronikus dokumentum]. Ed.: Paolo Soda, Francesco Tortorella, Sameer Antani, Mykola Pechenizkiy, Mario Cannataro, Alexey Tsymbal, IEEE, Piscataway, NJ, 1-4, 2012. ISBN: 9781467320498
  10. Qureshi, R., Kovács, L., Harangi, B., Nagy, B., Pető, T., Hajdu, A.: Combining algorithms for automatic detection of optic disc and macula in fundus images.
    Comput. vis. image underst. 116 (1), 138-145, 2012.
    Folyóirat-mutatók:
    Q1 Computer Vision and Pattern Recognition
    Q2 Signal Processing
    Q2 Software
  11. Szeghalmy, S., Tomán, H., Hajdu, A.: Detecting Digital Intersections Using Line Approximation.
    In: Proceedings of the 8th International Conference on Applied Informatics (ICAI2010) Vol. 1. / edited by Attila Egri-Nagy, Emőd Kovács, Gergely Kovásznai, Gábor Kusper, Tibor Tómács, Eszterházy Károly Főiskola, Eger, 193-202, 2011. ISBN: 9789639894723
  12. Tomán, H., Kovács, L., Jónás, Á., Hajdu, L., Hajdu, A.: Generalized Weighted Majority Voting with an Application to Algorithms Having Spatial Output.
    In: Hybrid Artificial Intelligent Systems. Ed.: Emilio Corchado, Václav Snášel, Ajith Abraham, Michał Woźniak, Manuel Graña, Sung-Bae Cho, Springer-Verlag Berlin Heidelberg, Heidelberg, 56-67, 2012, (Lecture Notes in Computer Science ; 7209) ISBN: 9783642289309
  13. Antal, B., Hajdu, A.: Improving microaneurysm detection using an optimally selected subset of candidate extractors and preprocessing methods.
    Pattern Recognit. 45 (1), 264-270, 2012.
    Folyóirat-mutatók:
    Q1 Artificial Intelligence
    D1 Computer Vision and Pattern Recognition
    D1 Signal Processing
    Q1 Software
  14. Harangi, B., Hajdu, A.: Improving the accuracy of optic disc detection by finding maximal weighted clique of multiple candidates of individual detectors.
    Proc. IEEE Int. Symp. Biomed. Imaging. 9 602-605, 2012.
  15. Harangi, B., Nagy, B., Hajdu, A.: Improving the detection of excessive activation of ciliaris muscle by clustering thermal images.
    In: Proceedings of the Conference of Quantitative InfraRed Thermography [elektronikus dokumentum]. Ed.: by Gennaro Cardone ISBN: 978890648441
  16. Antal, B., Lázár, I., Hajdu, A.: Mikroaneurizma-detektálás összetett rendszerrel.
    In: 8th Conference of the Hungarian Association for Image Processing and Pattern Recognition January 25-28, 2011 Szeged, Hungary : Proceedings of KÉPAF 2011. Szerk.: Zoltán Kató, Palágyi Kálmán, Erdőhelyi Balázs, Szegedi Egyetem, Szeged, 155-162, 2012.
  17. Tukacs, E., Korotij, Á., Maros-Szabó, Z., Molnár, Á., Hajdu, A., Török, Z.: Model requirements for Biobank Software Systems.
    Bioinformation. 8 (6), 290-292, 2012.
  18. Csutak, A., Török, Z., Tukacs, E., Maros-Szabó, Z., Csősz, É., Berta, A., Molnár, Á., Tőzsér, J., Nagy, V., Domokos, B., Hajdu, A.: Multimarkers for diabetic retinopathy screening.
    Acta Ophthalmol. 90 (S249), S037, 2012.
  19. Lázár, I., Hajdu, A.: Segmentation of Vessels in Retinal Images Based on Directional Height Statistics.
    Conf Proc IEEE Eng Med Biol Soc. 34 1458-1461, 2012.
2011
  1. Tomán, H., Kovács, L., Jónás, Á., Hajdu, L., Hajdu, A.: A Generalization of Majority Voting Scheme for Medical Image Detectors.
    In: Hybrid Artificial Intelligent Systems : 6th international conference, HAIS 2011, Wroclaw, Poland, May 23-25, 2011; proceedings. Eds.: Emilio Corchado, Marek Kurzynski, Michal Wozniak, Springer, Heidelberg [etc.], 189-196, 2011, (Lecture Notes in Computer Science ; 6679.) ISBN: 9783642212215
  2. Antal, B., Hajdu, A.: An ensemble-based microaneurysm detector for retinal images.
    Proc. Int. Conf. Image Proc. 2011 1621-1624, 2011.
  3. Antal, B., Hajdu, A.: A stochastic approach to improve macula detection in retinal images.
    Acta Cybern. 20 (1), 5-15, 2011.
    Folyóirat-mutatók:
    Q4 Computational Theory and Mathematics
    Q3 Computer Science (miscellaneous)
    Q3 Computer Vision and Pattern Recognition
    Q3 Electrical and Electronic Engineering
    Q3 Information Systems and Management
    Q4 Management Science and Operations Research
    Q3 Software
    Q4 Theoretical Computer Science
  4. Qureshi, R., Kovács, L., Nagy, B., Harangi, B., Hajdu, A.: Automatic detection of the fovea and optic disk in digital retinal images by combining algorithms.
    In: Proceedings of the 8th International Conference on Applied Informatics. Ed.: Attila Egri-Nagy, Emőd Kovács, Gergely Kovásznai, Gábor Kusper, Tibor Tómács, Eszterházy K. College, Eger, 175-184, 2011. ISBN: 9789639894723
  5. Harangi, B., Csordás, T., Hajdu, A.: Detecting the excessive activation of the ciliaris muscle on thermal images.
    In: Proceedings of 9th IEEE International Symposium on Applied Machine Intelligence and Informatics, University of Smolenice, Smolenice, 329-332, 2011. ISBN: 9781424474288
  6. Harangi, B., Csordás, T., Hajdu, A.: Detecting the excessive activation of the ciliaris muscle on thermal images.
    In: International Conference on Applied Informatics (8)(2010.01.27-2010.01.30)(Eger), Eszterházy K. College, Eger, 449-450, 2011. ISBN: 9789639894723
  7. Csutak, A., Antal, B., Lázár, I., Pető, T., Török, Z., Biró, A., Hajdu, A.: Diabetic retinopathy screening with computational support.
    Acta Ophthalmol. 89 357, 2011.
  8. Nagy, B., Harangi, B., Antal, B., Hajdu, A.: Ensemble-based exudate detection in color fundus images.
    Proc. Int. Symp. Image. Signal. Process. Anal. 700-703, 2011.
  9. Antal, B., Lázár, I., Hajdu, A., Török, Z., Csutak, A., Pető, T.: Evaluation of the grading performance of an ensemble-based microaneurysm detector.
    Conf Proc IEEE Eng Med Biol Soc. 2011 5943-5946, 2011.
  10. Kovács, G., Fazekas, A., Hajdu, A.: Exponential contrast maximization of intensity images.
    In: Proceedings of the 7th International Symposium on Image and Signal Processing and Analysis, Dubrovnik, Croatia, September 4-6, 2011. Eds.: S. Lončarić, G. Ramponi, D. Seršić, IEEE, Danvers, 139-142, 2011. ISBN: 9789531841597
  11. Kovács, G., Hajdu, A.: Extraction of vascular system in retina images using averaged one-dependence estimators and orientation estimation in Hidden Markov Random Fields.
    In: 2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro. Proceedings, IEEE, Piscataway, 693-696, 2011, (ISSN 1945-7936) ISBN: 9781424441280
  12. Kovács, L., Harangi, B., Nagy, B., Qureshi, R., Hajdu, A.: Gráf alapú vakfolt és sárgafolt detektálás retina felvételeken.
    In: 8th Conference of the Hungarian Association for Image Processing and Pattern Recognition January 25-28, 2011 Szeged, Hungary : Proceedings of KÉPAF 2011. Szerk.: Zoltán Kató, Palágyi Kálmán, Erdőhelyi Balázs, Szegedi Egyetem, Szeged, 329-341, 2011.
  13. Lázár, I., Hajdu, A.: Microaneurysm detection in retinal images using a rotating cross-section based model.
    Proc. IEEE Int. Symp. Biomed. Imaging. 1405-1409, 2011.
  14. Antal, B., Lázár, I., Hajdu, A.: Novel approaches to improve microaneurysm detection in retinal images.
    In: Proceedings of The 8th International Conference on Applied Informatics : Eger, Hungary, January 27 - 30, 2010. Ed.: Attila Egri-Nagy [et al.], [Eszterházy Károly Főiskola], [Eger], 117-124, [2011].
2010
  1. Antal, B., Lázár, I., Hajdu, A., Török, Z., Csutak, A., Pető, T.: A multi-level ensemble-based system for detecting microaneurysms in fundus images.
    In: Soft Computing Applications (SOFA), 2010 4th International Workshop on, [s.n.], Arad, Románia, 137-142, 2010. ISBN: 9781424479856
  2. Antal, B., Lázár, I., Hajdu, A.: An optimal voting scheme for microaneurysm candidate extractors using simulated annealing.
    In: 5th International Conference on Signal Processing and Multimedia Applications : SIGMAP 2010, IEEE, Athén, 80-87, 2010.
  3. Lázár, I., Qureshi, R., Hajdu, A.: A Novel Approach for the Automatic Detection of Microaneurysms in Retinal Images.
    In: Proceedings of the Emerging Technologies (ICET), 2010 6th International Conference on, IEEE, Piscataway, 193-197, 2010. ISBN: 9781424480579
  4. Antal, B., Hajdu, A., Csutak, A., Pető, T.: A two-phase pre-filtering approach to the automatic screening of digital fundus images.
    In: 5th International Conference on Signal Processing and Multimedia Applications : SIGMAP 2010, [s.n.], Athén, Görögország, 155-158, 2010.
  5. Harangi, B., Qureshi, R., Csutak, A., Pető, T., Hajdu, A.: Automatic Detection Of The Optic Disc Using Majority Voting In A Collection Of Optic Disc Detectors.
    Proc. IEEE Int. Symp. Biomed. Imaging. 1329-1332, 2010.
  6. Hajdu, A., Qureshi, R., Pető, T., Nagy, B., Kovács, L., Harangi, B.: Detection of the optic disc and the macula through combining algorithms.
    Faculty of Informatics, Debrecen, 17 p., 2010.
  7. Kovács, L., Qureshi, R., Nagy, B., Harangi, B., Hajdu, A.: Graph Based Detection of Optic Disc and Fovea in Retinal Images.
    In: Proceedings of IEEE 4th International Workshop on Soft Computing Applications, Arad-Romania, IEEE 4th International Workshop on Soft Computing Applications, Arad-Romania, 143-148, 2010. ISBN: 9781424479856
  8. Antal, B., Hajdu, A.: Improving microaneurysm detection in color fundus images by using an optimal combination of preprocessing methods and candidate extractors.
    In: 18th European Signal Processing Conference, [s.n.], Aalborg, Dánia, 1224-1228, 2010.
  9. Lázár, I., Hajdu, A.: Retinal Microaneurysm Detection Based on Intensity Profile Analysis.
    In: Proceedings of the 8th International Conference on Applied Informatics (ICAI2010) Vol. 1. / edited by Attila Egri-Nagy, Emőd Kovács, Gergely Kovásznai, Gábor Kusper, Tibor Tómács, Eszterházy Károly Főiskola, Eger, 157-165, 2011. ISBN: 9789639894723
  10. Tomán, H., Hajdu, A., Szakács, J., Hornyik, D., Csutak, A., Pető, T.: Thickness-based binary morphological improvement of distorted digital line intersections.
    In: Proceedings of the Fifth Hungarian Conference on Computer Graphics and Geometry, SZTAKI, Budapest, 133-139, 2010.
2009
  1. Harangi, B., Csordás, T., Hajdu, A.: A ciliaris izom túlzott működésének vizsgálata szomatoinfrával készített képeken.
    In: Proceedings of the 7th Conference of the Hungarian Association for Image Processing and Pattern Recognition. January 28-30, 2009, Budapest, Hungary [elektronikus dokumentum], MTA SZTAKI, Budapest, 1-8, 2009.
  2. Antal, B., Hajdu, A.: A prefiltering approach for an automatic screening system.
    In: IEEE 6th International Symposium on Intelligent Signal Processing (WISP2009), 26-28 August 2009, Budapest, Hungary, IEEE, Piscataway, N.J, 265-268, 2009.
  3. Hajdu, A., Pitas, I.: Digital curve compression based on graph theory.
    In: Proceedings of the 7th Conference of the Hungarian Association for Image Processing and Pattern Recognition. January 28-30, 2009, Budapest, Hungary [elektronikus dokumentum], MTA SZTAKI, Budapest, 1-10, 2009.
  4. Hajdu, A., Pető, T., Bíró, A., Harangozó, R., Hülvely, J., Török, Z., Csutak, A.: Extracting metadata from fundus images for the screening of diabetic retinopathy.
    In: IEEE 6th International Symposium on Intelligent Signal Processing (WISP2009), 26-28 August 2009, Budapest, Hungary, IEEE, Piscataway, N.J, 259-263, 2009.
  5. Hajdu, A., Veres, P., Tanács, A., Pető, T., Harangozó, R., Hülvely, J., Török, Z., Bíró, A., Csutak, A.: Model-based subsampling: applications.
    In: Proceedings of the 7th Conference of the Hungarian Association for Image Processing and Pattern Recognition. January 28-30, 2009, Budapest, Hungary [elektronikus dokumentum], MTA SZTAKI, Budapest, 1-8, 2009.
  6. Hajdu, A., Veres, P., Pitas, I.: Model-based subsampling: theory.
    In: Proceedings of the 7th Conference of the Hungarian Association for Image Processing and Pattern Recognition. January 28-30, 2009, Budapest, Hungary [elektronikus dokumentum], MTA SZTAKI, Budapest, 1-8, 2009.
  7. Hajdu, A., Veres, P., Tanács, A., Harangozó, R.: Object subsampling strategies to improve computational performance.
    Proc Int Symp Image Signal Process Anal. 6 448-453, 2009.
  8. Harangozó, R., Veres, P., Hajdu, A.: Subsampling strategies to improve learning-based retina vessel segmentation.
    Proc. Int. Conf. Image Proc. 16 3349-3352, 2009.
2008
  1. Fazekas, A., Hajdu, A., Sajó, L., Kovács, G.: A digitális képfeldolgozás területén folyó kutatások a Debreceni Egyetem Informatika Karán.
    In: Informatika a felsőoktatásban 2008, Debrecen, 2008. augusztus 27-29. [elektronikus dokumentum]. Szerk.: Pethő Attila, Herdon Miklós, Debreceni Egyetem, Informatikai Kar, Debrecen, 1-8, 2008. ISBN: 9789634731290
  2. Hajdu, A., Tóth, T.: Approximating non-metrical Minkowski distances in 2D.
    Pattern Recognit. Lett. 29 (6), 813-821, 2008.
    Folyóirat-mutatók:
    Q1 Artificial Intelligence
    Q1 Computer Vision and Pattern Recognition
    Q1 Signal Processing
    Q1 Software
  3. Hajdu, A., Pitas, I.: Piecewise linear digital curve representation and compression using graph theory and a line segment alphabet.
    IEEE Trans. Image Process. 17 (2), 126-133, 2008.
    Folyóirat-mutatók:
    D1 Computer Graphics and Computer-Aided Design
    D1 Software
  4. Hajdu, A., Veres, P., Tanács, A., Pitas, I.: Simplification of objects for faster registration.
    In: International conference "Numerical geometry, grid generation and scientific computing" (NUMGRID2008) and "Voronoi-2008" workshop, Moscow, Russia, June 10-13, 2008 [elektronikus dokumentum], [International conference "Numerical geometry, grid generation and scientific computing" (NUMGRID2008) & "Voronoi-2008" workshop], [Moscow, Russia], 2, 2008.
2007
  1. Hajdu, A., Tóth, T.: Approximating Non-Metrical Minkowski Distances in 2D.
    In: 6th Conference of the Hungarian Association for Image Processing and Pattern Recognition (KÉPAF 2007) January 25-27 2007, Debrecen, Hungary [Elektronikus dokumentum]. Szerk.: Fazekas Attila, Hajdu András, [Képfeldolgozók és Alakfelismerők Társasága], [s. l.], 54-62, 2007.
  2. Hajdu, A., Pitas, I.: Compression optimized tracing of digital curves using graph theory.
    In: International Conference on Image Processing (IEEE ICIP 2007) September 16-19, 2007, San Antonio, Texas, USA, Institute of Electrical and Electronics Engineers, Piscataway, New Jersey, 453-456, 2007.
  3. Hajdu, A., Pitas, I.: Content adaptive heterogeneous snakes.
    In: International Conference on Image Processing (IEEE ICIP 2007) September 16-19, 2007, San Antonio, Texas, USA, Institute of Electrical and Electronics Engineers, Piscataway, New Jersey, 253-256, 2007.
  4. Hajdu, A., Veres, P., Tóth, T.: Discrete approximations of non-metrical distances.
    In: Fourth hungarian conference on computer graphics and geometry, November 13-14, 2007 SZTAKI, Budapest, Hungary, [közread. Fourth hungarian conference on computer graphics and geometry], [Budapest], 164-171, 2007.
  5. Hajdu, A., Tijdeman, R., Hajdu, L.: General neighborhood sequences in Zn.
    Discrete Appl. Math. 155 (18), 2507-2522, 2007.
    Folyóirat-mutatók:
    Q2 Applied Mathematics
    Q2 Discrete Mathematics and Combinatorics
  6. Hajdu, A., Giamas, C., Vretos, N., Pitas, I.: Metadata description of thermal videos for rescue operations.
    In: ISSCS 2007, 8th International Symposium on Signals, Circuits, and Systems, July 12-13, 2007, Iasi, Romania, Vol. 2, IEEE, Piscataway, NJ, 325-328, 2007.
  7. Hajdu, A., Giamas, C., Pitas, I.: Object simplification using skeleton-based weight function.
    In: ISSCS 2007, 8th International Symposium on Signals, Circuits, and Systems, July 12-13, 2007, Iasi, Romania, Vol. 2, IEEE, New Jersey, 1-4, 2007.
  8. Hajdu, A., Pitas, I.: Optimal approach for fast object-template matching.
    IEEE Trans. Image Process. 16 (8), 2048-2057, 2007.
    Folyóirat-mutatók:
    D1 Computer Graphics and Computer-Aided Design
    D1 Software
  9. Fazekas, A., Hajdu, A., Hajdu, L.: Properties of a natural ordering relation for octagonal neighborhood sequences.
    In: 5th International Symposium on Image and Signal Processing and Analysis, IEEE Computer Society, Istanbul, 168-173, 2007.
  10. Hajdu, A., Veres, P., Tanács, A.: Simplification of objects for adaptive matching and visualization.
    In: Fourth hungarian conference on computer graphics and geometry, November 13-14, 2007 SZTAKI, Budapest, Hungary, [Fourth hungarian conference on computer graphics and geometry], [Budapest], 164-171, 2007.
  11. Hajdu, A., Giamas, C., Pitas, I.: Thermal video processing support for rescue operations.
    In: 6th Conference of the Hungarian Association for Image Processing and Pattern Recognition (KÉPAF 2007) January 25-27 2007, Debrecen, Hungary [Elektronikus dokumentum]. Szerk.: Fazekas Attila, Hajdu András, [Képfeldolgozók és Alakfelismerők Társasága], [s. l.], 207-211, 2007.
2006
  1. Asteriadis, S., Nikolaidis, N., Hajdu, A., Pitas, I.: An Eye Detection Algorithm Using Pixel to Edge Information.
    In: Second International Symposium on Communications, Control and Signal Processing (ISCCSP 2006), 13 - 15 March 2006, Marrakech, Morocco, SuviSoft Oy, Tampere, [4], 2006. ISBN: 9782908849172
  2. Asteriadis, S., Nikolaidis, N., Hajdu, A., Pitas, I.: A novel eye-detection algorithm utilizing edge-related geometrical information.
    In: 14th European Signal Processing Conference ; September 4 - 8, 2006, Florence, Italy (EUSIPCO 2006) [Elektronikus dokumentum]. Ed.: EURASIP, European Association for Signal Processing, [s.n.], Florence, [5], 2006.
  3. Hajdu, A., Kormos, J., Tóth, T., Veréb, K.: Applications of neighborhood sequence in image processing and database retrieval.
    J. Univ. Comp. Sci. 12 (9), 1240-1253, 2006.
    Folyóirat-mutatók:
    Q2 Computer Science (miscellaneous)
    Q3 Theoretical Computer Science
  4. Roubies, A., Hajdu, A., Pitas, I.: Improving the performance of the GVF snake algorithm.
    In: Second International Symposium on Communications, Control and Signal Processing (ISCCSP 2006), 13 - 15 March 2006, Marrakech, Morocco [elektronikus dokumentum]. Ed.: IEEE, EURASIP, SuviSoft, Tampere (Finlande), 4, 2006.
  5. Hajdu, A., Tóth, T., Veréb, K.: Neighborhood sequences for comparing similarity vectors in image retrieval.
    In: Summer University on Information Technology in Agriculture and Rural Development, Proceedings SU2006 conference, Debrecen, Hungary, 21-22. August. 2006, Hungarian Association of Agricultural Informatics, Debrecen, 118-123, 2006.
  6. Hajdu, A., Hajdu, L.: On the lattice structure of subsets of octagonal neighborhood sequences in Zn.
    In: Discrete geometry for computer imagery: 13th international conference, DGCI 2006, Szeged, Hungary, October 25-27, 2006 : proceedings / Attila Kuba, László G. Nyúl, Kálmán Palágyi (eds.), Springer, Berlin, Heidelberg, 211-222, 2006, (Lecture notes in computer science, ISSN 0302-9743, 4245/2006)
  7. Hajdu, A., Roubies, A., Pitas, I.: Optimized chamfer matching for snake-based image contour representations.
    In: 2006 IEEE International conference on multimedia and expo ICME 2006 : proceedings, July 9-12, 2006, Hilton Toronto, Ontario, Canada, IEEE Operations Center, Piscataway, New Jersey, 1017-1020, 2006.
  8. Hajdu, A., Kormos, J., Lencse, Z., Trón, L., Emri, M.: The "MEDIP - Platform independent software system for medical image processing" project.
    J. Univ. Comp. Sci. 12 (9), 1229-1239, 2006.
    Folyóirat-mutatók:
    Q2 Computer Science (miscellaneous)
    Q3 Theoretical Computer Science
2005
  1. Emri, M., Hajdu, A., Kormos, J., Lencse, Z.: A "Medip - platformüggetlen szoftver keretrendszer orvosi képfeldolgozáshoz" projekt bemutatása = the "Medip platform independent software system for medical image processing" project.
    In: Informatika a felsőoktatásban 2005 : konferencia kiadvány : Debrecen, 2005 augusztus 24-26.. Szerk.: Pethő Attila, Herdon Miklós, Debreceni Egyetem Informatikai Kar, Debrecen, , 2005.
  2. Hajdu, A., Fazekas, A., Hajdu, L.: Lattices of metrical neighborhood sequences.
    In: Joint Hungarian-Austrian Conference on Image Processing and Pattern Recognition (HACIPPR 2005), Veszprém, Hungary, 11-13. May, 2005, [s.n.], [s.l.], 143-147, 2005.
  3. Fazekas, A., Hajdu, A., Hajdu, L.: Metrical neighborhood sequences in Zn.
    Pattern Recognit. Lett. 26 (13), 2022-2032, 2005.
    Folyóirat-mutatók:
    Q2 Artificial Intelligence
    Q2 Computer Vision and Pattern Recognition
    Q2 Signal Processing
    Q2 Software
  4. Hajdu, A., Kormos, J., Lukács, A., Pányik, Á., Szabó, C., Veres, P., Zörgő, Z.: Multipurpose 3D modeling for virtual clinical interventions.
    In: 2nd International Conference on Computational Intelligence in Medicine and Healthcare (CIMED 2005), [S.n.], Lisbon, 7, 2005.
  5. Fazekas, A., Hajdu, A., Sánta, I., Tóth, T.: Neighborhood sequences and their applications in the digital image processing.
    In: Computer Analysis of Images and Patterns : 11th International Conference, CAIP 2005, Versailles, France, September 5-8, 2005. Proceedings, Springer, Berlin; Heidelberg, 766-772, 2005, (Lecture Notes in Computer Science, ISSN 0302-9743 ; 3691.)
  6. Hajdu, A., Tóth, T., Veréb, K.: Novel approach for comparing similarity vectors in image retrieval.
    In: Joint Hungarian-Austrian Conference on Image Processing and Pattern Recognition (HACIPPR 2005) (2005), Veszprém, Hungary, 11-13. May, 2005
  7. Hajdu, A., Hajdu, L., Tóth, T.: Properties and Applications of Neighborhood Sequences.
    In: Third Hungarian Conference on Computer Graphics and Geometry, Budapest, Hungary, 17-18. November, 2005
  8. Hajdu, A., Kormos, J., Zörgő, Z.: Statistical analysis of distance functions for digital image processing applications.
    In: Proceedings of the 6th International Conference on Applied Informatics : January 27-31, 2004, Eger-Noszvaj. Szerk.: Csőke Lajos, [EKF], [Eger], 499, 2005.
  9. Hajdu, A., Kormos, J., Tóth, T., Veréb, K.: Szomszédsági szekvenciák és alkalmazásaik a képfeldolgozásban és képi adatbázisokban = neighborhood sequences and their applications in image processing and image databases.
    In: Informatika a felsőoktatásban 2005 : konferencia kiadvány : Debrecen, 2005 augusztus 24-26.. Szerk.: Pethő Attila, Herdon Miklós, Debreceni Egyetem Informatikai Kar, Debrecen, 10-15, 2005.
2004
  1. Csernátony, Z., Hajdu, A., Manó, S., Zörgő, Z.: 3D modell készítése ortopédiai műtétek szimulálásához.
    In: Képfeldolgozók és alakfelismerők IV. konferenciája : Miskolc-Tapolca, 2004. január 28-30, NJSZT-KÉPAF, Budapest, 43-49, 2004.
  2. Hajdu, A., Hajdu, L.: Analytical and approximation properties of neighborhood sequences.
    In: Képfeldolgozók és alakfelismerők IV. konferenciája : Miskolc-Tapolca, 2004. január 28-30, NJSZT-KÉPAF, Budapest, 97-105, 2004.
  3. Hajdu, A., Zörgő, Z.: ANSYS for Virtual Surgery: FEA is a valuable tool that aids doctors in orthopedic operations.
    ANSYS Solutions Summer 2004 summer 2004 10-13, 2004.
  4. Hajdu, A., Hajdu, L.: Approximating the euclidean distance using nonperiodic neighbourhood sequences.
    Disc. Math. 283 (1-3), 101-111, 2004.
    Folyóirat-mutatók:
    Q2 Discrete Mathematics and Combinatorics
    Q1 Theoretical Computer Science
  5. Hajdu, A., Nagy, B., Zörgő, Z., Kormos, J.: Choosing appropriate distance measurement in digital image segmentation.
    Annales Univ. Sci. Budapest., Sect. Comp. 24 193-208, 2004.
  6. Hajdu, A., Tóth, T., Veréb, K., Zörgő, Z.: Distance functions in multidimensional image processing applications.
    In: Képfeldolgozók és alakfelismerők IV. konferenciája : Miskolc-Tapolca, 2004. január 28-30, NJSZT-KÉPAF, Budapest, 106-111, 2004.
  7. Hajdu, A., Kormos, J., Zörgő, Z.: Finding optimal distance functions for statistical image segmentation.
    In: 6th World Congress of the Bernoulli Society for Mathematical Statistics and Probability (2004), Barcelona, Spain, [6th World Congress of the Bernoulli Society for Mathematical Statistics and Probability], [Barcelona], 128, 2004.
  8. Hajdu, A., Hodnics, M., Kovács, K., Ungvári, A.: Gépi látáson alapuló rendszerek humán felhasználói környezetben: A Török 2.
    In: Képfeldolgozók és alakfelismerők IV. konferenciája : Miskolc-Tapolca, 2004. január 28-30, NJSZT-KÉPAF, Budapest, 112-117, 2004.
  9. Fazekas, A., Hajdu, A., Kormos, J., Kollár, L., Zörgő, Z., Veréb, K.: Intelligent urban traffic development support system: the simulation software and the database.
    In: Proceedings of the 6th International Conference on Applied Informatics : January 27-31, 2004, Eger, Hungary. Ed.: by Lajos Csőke, [Eszterházy Károly Főiskola], [Eger], 17-26, 2004.
  10. Hajdu, A., Hodnics, M., Kovács, K., Ungvári, A.: Machine vision systems in human user environments: The Turk 2.
    In: Norwegian Conference on Image Processing and Pattern Recognition (NOBIM 2004), Stavanger, Norway, 27-28 May 2004
  11. Emri, M., Hajdu, A., Kormos, J., Lencse, Z.: MEDIP: platformfüggetlen szoftver keretrendszer orvosi képfeldolgozáshoz.
    IME. 3 (5), 44-48, 2004.
  12. Hajdu, A., Manó, S., Zörgő, Z.: The "spiral cut" technique for leg lengthening.
    In: Proceedings of the First Hungarian Conference on Biomechanics, Budapest, Hungary June 11-12, 2004, Biomechanikai Kutatóközpont, [Budapest], 151-160, 2004.
2003
  1. Zörgő, Z., Hajdu, A., Manó, S., Csernátony, Z., Molnár, S.: Analyzis of a new femur lengthening surgery.
    In: Proceedings of the IASTED International Conference on Biomechanics : June 30 - July 2, 2003, Rhodes, Greece (BioMech 2003), ACTA Press, Greece, 34-38, 2003.
  2. Hajdu, A.: Geometry of neighbourhood sequences.
    Pattern Recognit. Lett. 24 (15), 2597-2606, 2003.
    Folyóirat-mutatók:
    Q2 Artificial Intelligence
    Q2 Computer Vision and Pattern Recognition
    Q3 Signal Processing
    Q2 Software
  3. Hajdu, A., Nagy, B., Zörgő, Z.: Indexing and segmenting colour images using neighbourhood sequences.
    In: ICIP-2003 : 2003 International Conference on Image Processing : proceedings : September 14-17, 2003, Barcelona, Spain, IEEE, Piscataway, New Jersey, 957-960, 2003.
  4. Fazekas, A., Hajdu, A., Hajdu, L.: Lattice of generalized neighbourhood sequences in nD.
    In: ISPA 2003 : proceedings of the 3nd International Symposium on Image and Signal Processing and Analysis : Rome, Italy, September 18-20, 2003, Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia, 107-111, 2003.
  5. Hajdu, A., Hajdu, L.: Velocity and distance of neighbourhood sequences.
    Acta Cybern. 16 (1), 133-145, 2003.
    Folyóirat-mutatók:
    Q4 Computational Theory and Mathematics
    Q3 Computer Science (miscellaneous)
    Q3 Computer Vision and Pattern Recognition
    Q3 Electrical and Electronic Engineering
    Q3 Information Systems and Management
    Q4 Management Science and Operations Research
    Q3 Software
    Q4 Theoretical Computer Science
2002
  1. Hajdu, A., Kormos, J.: A Debreceni Egyetem intézeteinek együttműködése különböző képfeldolgozási projektekben = cooperation among the institutes of the University of Debrecen in digital image processing projects.
    In: Informatika a felsőoktatásban : 2002 : konferenciakiadvány : Debrecen, 2002. aug. 28-30.. Szerk.: Arató Péter, Herdon Miklós, Debreceni Egyetem, Debrecen, 773-780, 2002.
  2. Fazekas, A., Hajdu, A., Kormos, J., Fazekas, G.: A digitális képfeldolgozás oktatásának eredményei és néhány aktuális kérdése a Debreceni Egyetemen.
    In: Informatika a felsőoktatásban : 2002 : konferenciakiadvány : Debrecen, 2002. aug. 28-30. Szerk.: Arató Péter, Herdon Miklós, Debreceni Egyetem, Debrecen, 758-765, 2002. ISBN: 9634726917
  3. Hajdu, A., Nagy, B.: Approximating the Euclidean circle using neighbourhood sequences.
    In: Képfeldolgozók és alakfelismerők III. konferenciája, Domaszék, 2002. január 23-25.. Szerk.: Kuba Attila, Máté Eörs, Palágyi Kálmán, Neumann János Számítógéptudományi Társaság, [Budapest], 260-271, 2002.
  4. Fazekas, A., Hajdu, A.: Extracting Feature Vectors for Character Recognition by Walsh Transformation.
    In: Képfeldolgozók és alakfelismerők III. konferenciája, Domaszék, 2002. január 23-25.. Szerk.: Kuba Attila, Máté Eörs, Palágyi Kálmán, Neumann János Számítógéptudományi Társaság, [Budapest], 272-278, 2002.
  5. Fazekas, A., Hajdu, L., Hajdu, A.: Lattice of generalized neighbourhood sequences in nD and (infinite)D.
    Publ. Math. Debrecen. 60 405-427, 2002.
    Folyóirat-mutatók:
    Q3 Mathematics (miscellaneous)
  6. Hajdu, A., Zörgő, Z.: Orvosi szoftver keretrendszer műtéti tervezéshez.
    In: Képfeldolgozók és alakfelismerők III. konferenciája, Domaszék, 2002. január 23-25.. Szerk.: Kuba Attila, Máté Eörs, Palágyi Kálmán, Neumann János Számítógéptudományi Társaság, [Budapest], 140-151, 2002.
2001
  1. Fazekas, A., Hajdu, A., Hajdu, L.: Analyzing the structure of the set of neighbourhood sequences.
    In: 5th international conference on applied informatics : January 28-February 3, 2001 Eger, Hungary. Szerk.: Kovács Emőd, Winkler Ferenc, Molnár és Társa 2001 Kft, Eger, 41-48, 2001.
  2. Fazekas, A., Hajdu, A., Hajdu, L.: Properties of generalized neighbourhood sequences in finite dimension.
    In: 4th international conference on applied informatics : Education and other fields of applied informatics : Computer graphics : Computer statistics and modeling : August 30-September 3, 1999 Eger-Noszvaj, Hungary. Szerk.: Kovács Emőd, Winkler Zoltán, Molnár és Társa`2001` Kft, Eger, 129-134, 2001.
  3. Fazekas, A., Hajdu, A.: Recognizing typeset documents using Walsh transformation.
    J. Comput. Inform. Tech. 9 (2), 101-112, 2001.
    Folyóirat-mutatók:
    Q3 Computer Science (miscellaneous)
2000
  1. Fazekas, A., Hajdu, A., Hajdu, L.: Véges dimenziós szekvenciák strukturális vizsgálata.
    In: Képfeldolgozók és alakfelismerők II. konferenciája, (KÉPAF 2) 2000, Noszvaj, Hungary, [Neumann János Számítógéptudományi Társaság], [Budapest], 29-32, 2000.
  2. Fazekas, A., Hajdu, A., Hajdu, L.: Végtelen dimenziós szekvenciák strukturális vizsgálata.
    In: Képfeldolgozók és alakfelismerők II. konferenciája, (KÉPAF 2) 2000, Noszvaj, Hungary, [Neumann János Számítógéptudományi Társaság], [Budapest], 33-36, 2000.
1999
  1. Baráz, Á., Fazekas, A., Hajdu, A., Jónás, R.: A gyakorlati feladatok szerepe a digitális képfeldolgozás oktatásában és megoldásukat támogató szoftverek.
    In: Informatika a felsőoktatásban : Konferencia kiadvány, [s. n.], Debrecen, 116-121, 1999.
  2. Fazekas, A., Hajdu, A.: An algorithm using Walsh transformation for compressing typeset documents.
    Acta Math. Acad. Paedagog. Nyíregyh. 15 61-68, 1999.
    Folyóirat-mutatók:
    Q4 Education
    Q4 Mathematics (miscellaneous)
1998
  1. Fazekas, A., Hajdu, A.: An algorithm using Walsh transformation for compressing typeset documents.
    Department of Mathematics and Informatics Lajos Kossuth University, Debrecen, 8 p., 1998.
  2. Fazekas, A., Hajdu, A.: Analysing the noise sensitivity of skeletonization algorithms.
    Department of Mathematics and Informatics Lajos Kossuth University, Debrecen, 16 p., 1998.
  3. Fazekas, A., Hajdu, A.: Analysing the noise sensitivity of skeletonization process.
    In: Conference of PhD students in computer science : volume of extended abstracts : CS 2 : July 18- 22, 1998, Szeged, Hungary. Ed.: Csendes Tibor, Unversity of Szeged, Szeged, 40, 1998.
1997
  1. Fazekas, A., Hajdu, A.: Analysing the noise sensitivity of skeletonization algorithms.
    Studia universitas "Babes-Bolyai" 2 55-70, 1997.
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