Convolutional Neural Network-Based Action Recognition on Depth Maps. - Jacek Trelinski; Bogdan Kwolek (ICCVG, 2018)

Ensemble of Classifiers Using CNN and Hand-Crafted Features for Depth-Based Action Recognition. - Jacek Trelinski; Bogdan Kwolek (ICAISC (2), 2019)

Multi-channels CNN temporal features for depth-based action recognition. - Jacek Trelinski; Bogdan Kwolek (ICMV, 2019)

Ensemble of Multi-channel CNNs for Multi-class Time-Series Classification. Depth-Based Human Activity Recognition. - Jacek Trelinski; Bogdan Kwolek (ACIIDS (1), 2020)

Deep Embedding Features for Action Recognition on Raw Depth Maps. - Jacek Trelinski; Bogdan Kwolek (ICCS (3), 2021)

Decision Combination in Classifier Committee Built on Deep Embedding Features. - Jacek Trelinski; Bogdan Kwolek (ICCCI, 2021)

Human Action Recognition on Raw Depth Maps. - Jacek Trelinski; Bogdan Kwolek (VCIP, 2021)

Embedded Features for 1D CNN-based Action Recognition on Depth Maps. - Jacek Trelinski; Bogdan Kwolek (VISIGRAPP (4: VISAPP), 2021)

CNN-based and DTW features for human activity recognition on depth maps. - Jacek Trelinski; Bogdan Kwolek (Neural Comput. Appl., 2021)

Enhancing Decision Combination in Classifier Committee via Positional Voting. - Jacek Trelinski; Bogdan Kwolek (ICCS (1), 2022)