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Hajdu András

Hajdu András

Hajdu András
DE > IK
egyetemi tanár, tanszékvezető 2008-
Név: Hajdu András
További profilok: Google Scholar, MTMT
Fokozat
  • PhD, Debreceni Egyetem (2003)
  • Habilitáció, Debreceni Egyetem (2008)
  • MTA doktora, MTA (2017)
Szakterület: matematikus, informatikus
Ajánlott linkek:
Önéletrajz: letöltés
Az adatok a NEPTUN rendszerből származnak.

Teljes publikációs lista

A lista áttöltése az MTMT rendszerébe
Hiányzó közlemények feltöltése
Hitelesített Publikációs Lista igénylése
OA letöltési statisztika megtekintése
Feltöltött közlemény:
182
DEA-ban:
173
OA:
17
Publikációs időszak:
1997-2021
2021
  1. Lantang, O., Terdik, G., Hajdu, A., Tiba, A.: Comparison of single and ensemble-based convolutional neural networks for cancerous image classification.
    Ann. Math. Inform. Epub 1-12, 2021.
    Folyóirat-mutatók:
    Q4 Computer Science (miscellaneous) (2020)
    Q4 Mathematics (miscellaneous) (2020)
  2. 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:
    Q4 Computer Science (miscellaneous) (2020)
    Q4 Mathematics (miscellaneous) (2020)
  3. 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:
    Q4 Computer Science (miscellaneous) (2020)
    Q4 Mathematics (miscellaneous) (2020)
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. 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
  3. 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. 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
  2. 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
  3. 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
  4. 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
  5. 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
  6. 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
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. 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)
  3. 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
  4. 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. 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
  3. 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
  4. 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
Mindet mutasd
frissítve: 2021-10-17, 01:07

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