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Tiba Attila

Tiba Attila

Tiba Attila
Név: Tiba Attila
További profilok: MTMT
Szakterület: matematikus, informatikus

Teljes publikációs lista

A lista áttöltése az MTMT rendszerébe
Hiányzó közlemények feltöltése
Hitelesített Publikációs Lista igénylése
OA letöltési statisztika megtekintése
Feltöltött közlemény:
18
DEA-ban:
18
OA:
7
Publikációs időszak:
2017-2024
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., Hajdu, A., Girászi, T.: Finding Efficient Graph Embeddings and Processing them by a CNN-based Tool.
    Neural Process Lett. 56 (5), 1-25, 2024.
    Folyóirat-mutatók:
    Q2 Artificial Intelligence (2023)
    Q2 Computer Networks and Communications (2023)
    Q3 Neuroscience (miscellaneous) (2023)
    Q2 Software (2023)
  4. 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. 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)
  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:
    Q3 Computer Science (miscellaneous)
    Q4 Mathematics (miscellaneous)
  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:
    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
frissítve: 2024-12-15, 01:09

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Tudományos folyóiratcikkek száma: 11
Q1 2 (18.2%)
Q2 4 (36.4%)
Q3 3 (27.3%)
n.a. 2 (18.2%)
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SCImago kategóriák

Computer Science (7)
Computer Science (miscellaneous) (4)
Artificial Intelligence (3)
Software (2)
Computer Networks and Communications (1)
Computer Science Applications (1)
Information Systems (1)
Mathematics (4)
Mathematics (miscellaneous) (4)
Medicine (2)
Health Informatics (1)
Oncology (1)
Biochemistry, Genetics and Molecular Biology (1)
Cancer Research (1)
Business, Management and Accounting (1)
Management Information Systems (1)
Engineering (1)
Engineering (miscellaneous) (1)
Neuroscience (1)
Neuroscience (miscellaneous) (1)

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