Tudóstér: Tiba Attila publikációi

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feltöltött közlemény: 17 Open Access: 7
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 (2023)
    Q2 Computer Science Applications (2023)
    Q2 Information Systems (2023)
    Q2 Management Information Systems (2023)
  2. Bogacsovics, G., Harangi, B., Beregi-Kovács, M., Kupás, D., Lakatos, R., Serbán, N., Tiba, A., Tóth, J.: Assessing Conventional and Deep Learning-Based Approaches for Named Entity Recognition in Unstructured Hungarian Medical Reports.
    In: 2024 IEEE 22nd World Symposium on Applied Machine Intelligence and Informatics (SAMI). Ed.: Kovács Levente, Liberios Vokorokos, IEEE, Piscataway, 77-82, 2024. ISBN: 9798350317206
  3. Tiba, A., Bérczes, T., Bérczes, A., Zsuga, J.: Predicting Stroke Risk Based on ICD Codes Using Graph-Based Convolutional Neural Networks.
    Mathematics. 12 (12), 1-15, 2024.
    Folyóirat-mutatók:
    Q2 Computer Science (miscellaneous) (2023)
    Q2 Engineering (miscellaneous) (2023)
    Q2 Mathematics (miscellaneous) (2023)
2022
  1. 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
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. 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)
  3. 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)
  4. 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
  5. 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.
  6. 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
  7. 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)
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. 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
  5. Bérczes, A., Bérczes, T., Varga, I., Tiba, A., Zsuga, J.: Using Laplacian spectrum to analise the comorbidities network of hemorrhagic stroke.
    In: Proceedings of the 10th IEEE International Conference on Cognitive Infocommunications : CogInfoCom 2019. Szerk.: Péter Baranyi, IEEE-Inst Electrical Electronics Engineers Inc, Piscataway, 53-60, 2019. ISBN: 9781728147932
2017
  1. 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
feltöltött közlemény: 17 Open Access: 7
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