no code implementations • 27 Mar 2024 • Petros Toupas, Zhewen Yu, Christos-Savvas Bouganis, Dimitrios Tzovaras
Convolutional Neural Networks (CNNs) have demonstrated their effectiveness in numerous vision tasks.
no code implementations • 6 Dec 2023 • Petros Toupas, Georgios Tsamis, Dimitrios Giakoumis, Konstantinos Votis, Dimitrios Tzovaras
These robots heavily rely on Human Action Recognition (HAR) to interpret human actions and intentions.
no code implementations • 4 Sep 2023 • Alexander Montgomerie-Corcoran, Petros Toupas, Zhewen Yu, Christos-Savvas Bouganis
The YOLO family of models is considered the most efficient for object detection, having only a single model pass.
no code implementations • 31 May 2023 • Petros Toupas, Christos-Savvas Bouganis, Dimitrios Tzovaras
A variety of 3D CNN models were evaluated using the proposed toolflow on multiple FPGA devices, demonstrating its potential to deliver competitive performance compared to earlier hand-tuned and model-specific designs.
no code implementations • 29 May 2023 • Petros Toupas, Christos-Savvas Bouganis, Dimitrios Tzovaras
3D Convolutional Neural Networks are gaining increasing attention from researchers and practitioners and have found applications in many domains, such as surveillance systems, autonomous vehicles, human monitoring systems, and video retrieval.
2 code implementations • 30 Mar 2023 • Petros Toupas, Alexander Montgomerie-Corcoran, Christos-Savvas Bouganis, Dimitrios Tzovaras
For Human Action Recognition tasks (HAR), 3D Convolutional Neural Networks have proven to be highly effective, achieving state-of-the-art results.