Current challenges in multi-view computer vision. - Gabor Kertesz; Zoltan Vamossy (SACI, 2015)

Multiprocessing of an individual-cell based model for parameter testing. - Gabor Kertesz; Dániel Kiss; Anna Lovrics; Sándor Szénási; Zoltan Vamossy (SACI, 2016)

Vehicle Image Matching Using Siamese Neural Networks with Multi-Directional Image Projections. - Gabor Kertesz; Sándor Szénási; Zoltan Vamossy (SACI, 2018)

Multi-Directional Projection Transformations for Machine Learning based Object Matching. - Gábor Kertész; Sándor Szénási; Zoltán Vámossy (SACI, 2019)

Multi-Directional Image Projections with Fixed Resolution for Object Recognition and Matching - Gábor Kertész (2019)

One-Shot Re-identification using Image Projections in Deep Triplet Convolutional Network. - Gábor Kertész; Imre Felde (SoSE, 2020)

Metric Embedding Learning on Multi-Directional Projections. - Gábor Kertész (Algorithms, 2020)

Special Issue on Bio-Inspired Algorithms for Image Processing. - Sándor Szénási; Gábor Kertész (Algorithms, 2020)

Hungarian Traffic Sign Detection and Classification using Semi-Supervised Learning. - Levente Kovács; Gábor Kertész (SACI, 2021)

Comparative analysis of image projection-based descriptors in Siamese neural networks. - Gábor Kertész; Sándor Szénási; Zoltán Vámossy (Adv. Eng. Softw., 2021)

Statistical accident analysis supporting the control of autonomous vehicles. - Sándor Szénási; Gábor Kertész; Imre Felde; László Nádai (J. Comput. Methods Sci. Eng., 2021)

Utilization of IMU-Based Gesture Recognition in the Treatment of Diabetes. - Marcell Szántó; Gergo Strasser; László Szász; Lehel Dénes-Fazakas; György Eigner; Gábor Kertész; Levente Kovács (AQTR, 2022)

Control of Type 1 Diabetes Mellitus using direct reinforcement learning based controller. - Lehel Dénes-Fazakas; Máté Siket; Gábor Kertész; László Szilágyi; Levente Kovács; György Eigner (SMC, 2022)

Deep Metric Learning Using Negative Sampling Probability Annealing. - Gábor Kertész (Sensors, 2022)

Birth time prediction based on uterus-activity using machine learning. - Gréta Gonda; Gábor Kertész (SACI, 2023)

Enhancing Diabetes Management Through GRU Analysis of Physical Activity Effects. - Barbara Simon; Ádám Hartvég; Máté Siket; Lehel Dénes-Fazakas; Levente Kovács; László Szilágyi; Gábor Kertész; György Eigner (SISY, 2024)

Achieving Peak Performance for Large Language Models: A Systematic Review. - Zhyar Rzgar K. Rostam; Sándor Szénási; Gábor Kertész (IEEE Access, 2024)

Fine-Tuning Large Language Models for Scientific Text Classification: A Comparative Study. - Zhyar Rzgar K. Rostam; Gábor Kertész (CoRR, 2024)

Turning LLM Activations Quantization-Friendly. - Patrik Czakó; Gábor Kertész; Sándor Szénási (SACI, 2025)

Addressing Activation Outliers in LLMs: A Systematic Review of Post-Training Quantization Techniques. - Patrik Czakó; Gábor Kertész; Sándor Szénási (IEEE Access, 2025)

Advancing Scientific Text Classification: Fine-Tuned Models with Dataset Expansion and Hard-Voting. - Zhyar Rzgar K. Rostam; Gábor Kertész (CoRR, 2025)

SmoothRot: Combining Channel-Wise Scaling and Rotation for Quantization-Friendly LLMs. - Patrik Czakó; Gábor Kertész; Sándor Szénási (CoRR, 2025)