Fazekas Attila

1.

Khudhair, M. A., Fazekas, A.: A Proposed Method to Reduce the Noise Sensitivity of Binary Classification Based on Robust Deep Neural Networks.
In: Proceedings of International Conference on Formal Methods and Foundations of Artificial Intelligence / Kovásznai Gergely, Eszterházy Károly Catholic University, Eger, 1-3, 2025.

DEA

2.

Fazekas, A., Kovács, G.: Enumerating the K-Fold Configurations in Multi-Class Classification Problems.
In: 2025 8th International Conference on Data Science and Machine Learning Applications (CDMA) / Basit Qureshi, Mohamed Alzamil, IEEE, New York, 14-17, 2025. ISBN: 9798331539702

DEA

3.

Palinszky, A., Fazekas, A.: Jupyter notebook - interaktív vizualizációs eszköz az oktatásban és a kutatásban.
In: Innovatív digitális módszerek az oktatás és kutatás területén / Kucsinka Katalin, Tiliscsák Olekszandr, Sztojka Miroszláv, Jakab Enikő, Papp Gabriella, Daróci Ádám, II. Rákóczi Ferenc Kárpátaljai Magyar Főiskola, Beregszász, Ukrajna, 190-193, 2025. ISBN: 9786178143367

DEA

4.

Fazekas, A.: Replikációs krizís jelensége a mesterséges intelligencia területén használt osztályozók esetében.
In: Innovatív digitális módszerek az oktatás és kutatás területén / Kucsinka Katalin, Tiliscsák Olekszandr, Sztojka Miroszláv, Jakab Enikő, Papp Gabriella, Daróci Ádám, II. Rákóczi Ferenc Kárpátaljai Magyar Főiskola, Beregszász, Ukrajna, 161-164, 2025. ISBN: 9786178143367

DEA

5.

Szeghalmy, S., Fazekas, A.: A comparative study on noise filtering of imbalanced data sets.
Knowledge-Based Syst. 301, 1-17, (article identifier: 112236), 2024.

doi DEA WoS Scopus

Journal metrics:

D1 Artificial Intelligence

Q1 Information Systems and Management

D1 Management Information Systems

D1 Software

6.

Fazekas, A., Szeghalmy, S.: Effect of Label-Noise Filtering on Classification of Imbalanced Data Sets with SVM.
In: Proceedings of the Future Technologies Conference (FTC) / Arai, Kohei, Springer, New York, 194-204, 2024, (Lecture Notes in Networks and SystemsISSN ; 1154) ISBN: 9783031731099

DEA Scopus

7.

Kovács, G., Fazekas, A.: mlscorecheck: Testing the consistency of reported performance scores and experiments in machine learning.
Neurocomputing. 583, 1-4, (article identifier: 127556), 2024.

doi DEA WoS Scopus

Journal metrics:

Q1 Artificial Intelligence

Q1 Cognitive Neuroscience

Q1 Computer Science Applications

8.

Fazekas, A., Kovács, G., Khudhair, M. A.: Reducing the Impact of the Reproducibility Crisis on the Ranking of Binary Classifiers through the Examination of Performance Scores' Consistency.
In: Book of Abstracts: Workshop on RECI 2024 / Elena Zaitseva, Peter Sedlacek, EDIS-Publishing House UNIZA, Zilina, Slovakia, 53-54, 2024. ISBN: 9788055421407

DEA

9.

Fazekas, A., Kovács, G.: Testing the consistency of performance scores reported for binary classification problems.
Appl. Soft. Comput. 164, 1-15, (article identifier: 111993), 2024.

doi DEA WoS Scopus

Journal metrics:

D1 Software

10.

Szeghalmy, S., Fazekas, A.: A Comparative Study of the Use of Stratified Cross-Validation and Distribution-Balanced Stratified Cross-Validation in Imbalanced Learning.
Sensors. 23 (4), 1-27, (article identifier: 2333), 2023.

doi DEA WoS Scopus

Journal metrics:

Q1 Analytical Chemistry

Q1 Atomic and Molecular Physics, and Optics

Q2 Biochemistry

Q2 Electrical and Electronic Engineering

Q2 Information Systems

Q1 Instrumentation

Q2 Medicine (miscellaneous)

11.

Fazekas, A., Kovács, G.: Optimal binning for a variance based alternative of mutual information in pattern recognition.
Neurocomputing. 519, 135-147, 2023.

doi DEA WoS Scopus

Journal metrics:

Q1 Artificial Intelligence

D1 Cognitive Neuroscience

D1 Computer Science Applications

12.

Szeghalmy, S., Fazekas, A.: A Highly Adaptive Oversampling Approach to Address the Issue of Data Imbalance.
Computers. 11 (5), 1-21, (article identifier: 73), 2022.

doi DEA WoS Scopus

Journal metrics:

Q2 Computer Networks and Communications

Q3 Human-Computer Interaction

13.

Kovács, G., Fazekas, A.: A new baseline for retinal vessel segmentation: Numerical identification and correction of methodological inconsistencies affecting 100+ papers.
Med. Image Anal. 75, 1-15, (article identifier: 102300), 2022.

doi DEA WoS Scopus

Journal metrics:

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

14.

Tóth, R., Tóth, B., Bodroginé Zichar, M., Fazekas, A., Hoffmann, M.: Detecting and Correcting Errors in Mental Cutting Test Intersections Computed with Blender.
In: ICGG 2022 - Proceedings of the 20th International Conference on Geometry and Graphics / Liang-Yee Cheng, Springer, Cham, 904-916, 2022. ISBN: 9783031135873

doi DEA WoS Scopus

15.

Tóth, R., Tóth, B., Bodroginé Zichar, M., Fazekas, A., Hoffmann, M.: Educational Applications to Support the Teaching and Learning of Mental Cutting Test Exercises.
In: ICGG 2022 - Proceedings of the 20th International Conference on Geometry and Graphics / Liang-Yee Cheng, Springer, Cham, 928-938, 2022. ISBN: 9783031135873

doi DEA WoS Scopus

16.

Szeghalmy, S., Fazekas, A.: Városi terepfelületek osztályozásának javítása mintavételezési módszerekkel.
In: Az elmélet és a gyakorlat találkozása a térinformatikában XII.: Theory meets practice in GIS. Szerk.: Molnár Vanda Éva, Debreceni Egyetemi Kiadó, Debrecen, 295-300, 2021. ISBN: 9789633189771

DEA

17.

Szeghalmy, S., Fazekas, A., Bodroginé Zichar, M., Bence, T. F., Uszkai, D.: Smartphone based Driver-Assistance System for Urban Environments.
In: The International Conference on Information and Digital Technologies 2019, IEEE, Zilina, 437-442, 2019. ISBN: 9781728114019

DEA

18.

Alhamzawi, H. A. M., Fazekas, A.: Assessment of Patients Emotional Status According To iris Movement.
In: Contemporary Computational Science : proceedings of the International Multi-Conference on Computational Science (CS 2018). Eds.: Piotr Kulczycki, Piotr A. Kowalski, Szymon Lukasik, AGH University of Science and Technology, Kraków, 160-176, 2018. ISBN: 9788366016224

DEA

19.

Bertók, K., Fazekas, A.: Facial gesture recognition and its applications.
In: Gesture recognition : performance, applications and features. Eds.: Gilberto Coleman, Roosevelt Ward, Nova Science Publishers, New York, 1-30, 2018. ISBN: 9781536134919

DEA

20.

Aszalós, L., Fazekas, A., Mihálydeák, T. S.: Kihívások és kényszerek - Új képzési programok a Debreceni Egyetem Informatikai Karán.
In: Informatika a felsőoktatásban 2017 konferencia kiadványa. Szerk.: Aradi Bernadett, Bujdosó Gyöngyi, Horváth Géza, Szokol Patrícia, Debreceni Egyetem Informatikai Kar, Debrecen, 101-108, 2017. ISBN: 9789634732136

DEA

21.

Németh, G., Kovács, G., Fazekas, A., Palágyi, K.: A Method for Quantitative Comparison of 2D Skeletons.
Acta Polytech. Hung. 13 (7), 123-142, 2016.

doi DEA WoS Scopus

Journal metrics:

Q2 Engineering (miscellaneous)

Q2 Multidisciplinary

22.

Bertók, K., Fazekas, A.: Face recognition on mobile platforms.
In: 7th IEEE International Conference on Cognitive Infocommunications: CogInfoCom 2016 : Proceedings. Szerk.: Péter Baranyi, IEEE Computer Society, Washington, 37-43, 2016.

doi DEA WoS Scopus

23.

Bertók, K., Fazekas, A.: Recognizing complex head movements.
Aust. J. Intell. Inform. Proccess. Syst. 14 (4), 3-17, 2016.

DEA

24.

Szalay, P. É., Szeghalmy, S., Kis, O., Szabó, L. J., Miskolczi, M., Fazekas, A., Dévai, G.: A sávos szitakötő [Calopteryx splendens (Harris, 1782)] konyári-kállói imágópopulációjának morfometriai elemzése.
Studia Odonatol. Hung. 17, 23-44, 2015.

DEA

25.

Szeghalmy, S., Bodroginé Zichar, M., Fazekas, A.: Gesture-based computer mouse using Kinect sensor.
In: 5th IEEE International Conference on Cognitive Infocommunications CogInfoCom 2014 : Proceedings, Vietri sul Mare, Italy. Ed.: Péter Baranyi, IEEE, Danvers, 419-424, 2014. ISBN: 9781479972807

doi DEA

Fazekas Attila

Publication list