S. Szénási, G. Légrádi: Machine learning aided metaheuristics: A comprehensive review of hybrid local search methods. EXPERT SYSTEMS WITH APPLICATIONS Vol. 258, Article No. 125192, pp. 1–14, 2024. ISSN 0957-4174 link Abstract: Machine learning-based methods have emerged as competitors to traditional metaheuristic-based solutions in many areas. Besides investigating their effectiveness, it raises the question of [...]

S. Szénási, G. Légrádi, B. Vígh: Machine Learning-Assisted Approach for Optimizing Step Size of Hill Climbing Algorithm. In IEEE 18th International Symposium on Applied Computational Intelligence and Informatics (SACI 2024) Proceedings. pp. 425–429, 2024. ISBN 979-8-3503-2952-0 link Abstract: Research on machine learning-assisted metaheuristics is a new and promising area for developing better optimization methods. This [...]

S. Tyagi, S. Szénási: Revolutionizing Speech Emotion Recognition: A Novel Hilbert Curve Approach for Two-Dimensional Representation and Convolutional Neural Network Classification. In Advances in Service and Industrial Robotics (Mechanisms and Machine Science). Cham, CH : Springer, pp. 75–85, 2024. ISSN 2211-0984, ISBN 978-3-031-59256-0 link Abstract: Emotions are integral to human existence, influencing psychological well-being and [...]

S. Tyagi, S. Szénási: Optimizing Speech Emotion Recognition with Deep Learning and Grey Wolf Optimization: A Multi-Dataset Approach. ALGORITHMS Vol. 17, No. 3, Article No. 90, pp. 1–15, 2024. ISSN 1999-4893 link Abstract: Machine learning and speech emotion recognition are rapidly evolving fields, significantly impacting human-centered computing. Machine learning enables computers to learn from data [...]

B. Holicza, P. Lehotay-Kéry, A. Kiss: Advancing in Protein Function Prediction: Leveraging Small Data Techniques in Convolutional and Graph Convolutional Networks. In 22nd IEEE International Symposium on Intelligent Systems and Informatics (SYSI 2024) Proceedings. pp. 405–410, 2024. ISBN 979-8-3503-8560-1 link Abstract: Protein function prediction is a crucial task in computational biology and bioinformatics, aiding in [...]

A. Jalili, H. Tabrizchi, A. Mosavi, A. R. Várkonyi-Kóczy: Enhancing Language Model Performance with a Novel Text Preprocessing Method. ACTA PHYSICA POLONICA A Vol. 146, No. 4, 2024. pp. 542–552. ISSN 0587-4246 link Abstract: Advances in natural language processing highlight the importance of text data preparation with machine learning. It has been reported that the [...]

D. T. Várkonyi, D. T. Bányai, A. R. Várkonyi-Kóczy: Investigating Traditional Machine Learning Models and the Utility of Audio Features for Lightweight Swarming Prediction in Beehives. ACTA POLYTECHNICA HUNGARICA Vol. 21, No. 10, 2024. pp. 283–299. ISSN 1785-8860 link Abstract: Remote monitoring of the status of beehives is essential for efficient beekeeping, leading to less [...]

B. Tusor, O. Takáč, S. Gubo, A. R. Várkonyi-Kóczy: Fuzzy Inference with Sequential Fuzzy Indexed Search Trees. In Recent Advances in Technology Research and Education (Lecture Notes in Networks and Systems 939). Cham, CH : Springer, pp. 294–304, 2024. ISSN 2367-3370, ISBN 978-3-031-54449-1 link Abstract: In this paper, a new method is presented for fuzzy [...]

B. Tusor, A. R. Várkonyi-Kóczy, S. Gubo: Improved Sequential Fuzzy Indexed Search Trees for Fast Classification. In IEEE International Symposium on Medical Measurements and Applications (MeMeA 2024) Proceedings. pp. 1–6, 2024. ISBN 979-8-3503-0800-6 link Abstract: Machine learning has been a significant part of computer science in the last few decades. The application of fuzzy inference [...]

L. Tamas, S. Gubo, T. Lukić: Vine Diseases Detection Trials in the Carpathian Region with Proximity Aerial Images. In IEEE 22th World Symposium on Applied Machine Intelligence and Informatics (SAMI 2024) Proceedings. pp. 29–33, 2024. ISBN 979-8-3503-1720-6 link Abstract: With the recent advances in the Agro 4.0 domain, the advanced inspection tools from the robotics [...]