Research group on MACHINE LEARNING

Faculty of Mathematics and Computer Science, Babes-Bolyai University, Romania

1. Sergiu Cosmin Nistor, Tudor Alexandru Ileni and Adrian Sergiu Darabant, Automatic Development of Deep Learning Architectures for Image Segmentation. Sustainability (2020), 12, 22,9707 (WoS, Q2)
2. Sergiu Cosmin Nistor. Multi-Staged Training of Deep Neural Networks for Micro-ExpressionRecognition. 2020 IEEE 14th International Symposium on Applied Computational Intelligenceand Informatics (SACI), pp. 000029-000034. IEEE, 2020.
3. M. Teletin, G. Czibula, CVSimP: An approach for predicting proteins' structural similarity using one-shot learning, IEEE 14th International Symposium on Applied Computational Intelligence and Informatics, SACI 2020, Timișoara, IEEE Computer Society, pp. 111-116 (indexed WoS)
4. L. Crivei, G. Czibula, G. Ciubotariu, M. Dindelegan, Unsupervised learning based mining of academic data sets for students’ performance analysis, IEEE 14th International Symposium on Applied Computational Intelligence and Informatics, SACI 2020, Timișoara, IEEE Computer Society, pp. 11-16 (indexed WoS)
5. I. A. Socaci, G. Czibula, V.S. Ionescu, A. Mihai, XNow: A deep learning technique for nowcasting based on radar products’ values prediction, IEEE 14th International Symposium on Applied Computational Intelligence and Informatics, SACI 2020, Timișoara, IEEE Computer Society, pp. 117-122 (indexed WoS)
6. S. Nițică, G. Czibula, V.-I. Tomescu, A comparative study on using unsupervised learning based data analysis techniques for breast cancer detection, IEEE 14th International Symposium on Applied Computational Intelligence and Informatics, SACI 2020, Timișoara, IEEE Computer Society, pp. 99-104 (indexed WoS)
7. A. Albu, G. Czibula, Analysing protein dynamics using machine learning based generative models, IEEE 14th International Symposium on Applied Computational Intelligence and Informatics, SACI 2020, Timișoara, IEEE Computer Society, pp. 135-140 (indexed WoS)
8. D.L. Miholca, G. Czibula, V.I. Tomescu, COMET: A conceptual coupling based metrics suite proposal for software defect prediction, 24nd International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES2020), Procedia Computer Science, Volume 176, 2020, Pages 31-40 (indexed WoS)
9. G. Czibula, A. Mihai, I.G. Czibula, RadRAR: A relational association rule mining approach for nowcasting based on predicting radar products' values, 24nd International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES2020), Procedia Computer Science, Vol. 176, pp. 300-309 (indexed WoS)
10. M. I. Bocicor, I. -M. Szuhai, E. -L. Pop and I. -G. Mircea, "Machine Learning based models for examining differences between modern and ancient DNA in dental calculus," 2020 22nd International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC), 2020, pp. 169-174, doi: 10.1109/SYNASC51798.2020.00036.
11. Vlad-Ioan Tomescu. FoRConvD: An approch for food recognition on mobile devicesusing convolutional neural networks and depth maps. IEEE 14th International Symposium on Applied Computational Intelligence and Informatics, SACI 2020, Timisoara, Romania, 2020, Pages 129–134.
12. Andrei Mihai. Using self-organizing maps as unsupervised learning models for meteorological data mining. IEEE 13th International Symposium on Applied Computational Intelligenceand Informatics, SACI 2020, Timioara, pp. 23–28