About us

Our research team in Computer Vision and Artificial Intelligence (CVAI) fundamentally focuses on advancing state-of-the-art deep learning algorithms such as object detection, tracking, video recognition, and Human Action Recognition (HAR) in combination with statistical analysis to develop intelligent and efficient algorithms for efficient visual analysis. Our novel deep-learning algorithms find applications in several domains including but not limited to virtual sports, automatic video surveillance, digital guard for smart cities, and border control. Our research team also investigates disruptive systems that use Distributed Ledger Technologies (DLT), with a focus on blockchain, to serve as a computational data resource for training machine learning and deep learning algorithms in applications where data privacy is of primary concern.

People

The group is directed by Huszár Viktor Dénes with Adhikarla Vamsi Kiran as a senior researcher and honorary associate professor Gábor Borsányi as an honorary member.

Facilities

CVAI has specialized research facilities for conducting innovative computer vision and artificial intelligence research including:

AI-related: Actors and tools to capture, process and compile high-quality databases to meet the specific needs of a research project, heavy-duty data servers with substantial memory, GPU resources, high-speed network connectivity, and optimized hardware for deep learning tasks.

Virtual and augmented reality equipment: As computer vision and AI continue to develop, virtual and augmented reality are becoming increasingly important tools for research. Research facilities also include virtual reality headsets, augmented reality devices, and haptic feedback systems.

Collaboration and communication tools: Our research facilities also include software tools for remote collaboration and project management tools.

Dataset

Sqiller-Spoof dataset

Publications

[1] Huszár, Viktor Dénes, and Vamsi Kiran Adhikarla. "Securing Phygital Gameplay: Strategies for Video-Replay Spoofing Detection." IEEE Access (2024).
[2] Huszár, Viktor Dénes, et al. "Towards Fast and Accurate Violence Detection for Automated Video Surveillance Applications." IEEE Access (2023).
[3] Huszár, Viktor. "Hamisítás észlelési módszerek az automatizált emberi tevékenység felismerésben." Hadtudomány 32.1 (2022): 270-284.
[4] Guindy, Mary, Vamsi K. Adhikarla, Peter A. Kara, Tibor Balogh, and Aniko Simon. "CLASSROOM: synthetic high dynamic range light field dataset." In Applications of Digital Image Processing XLV, vol. 12226, pp. 153-162. SPIE, 2022.
[5] Guindy, Mary, Attila Barsi, Peter A. Kara, Vamsi K. Adhikarla, Tibor Balogh, and Aniko Simon. "Camera animation for immersive light field imaging." Electronics 11, no. 17 (2022): 2689.
[6] Guindy, Mary, Adhikarla V. Kiran, Peter A. Kara, Tibor Balogh, and Aniko Simon. "Towards reconstructing HDR light fields by combining 2D and 3D CNN architectures." In Big Data IV: Learning, Analytics, and Applications, vol. 12097, pp. 192-197. SPIE, 2022.
[7] Guindy, Mary, Adhikarla V. Kiran, Péter A. Kara, Tibor Balogh, and Aniko Simon. "Performance evaluation of HDR image reconstruction techniques on light field images." In 2021 International Conference on 3D Immersion (IC3D), pp. 1-7. IEEE, 2021.
[8] Huszár, V.D. and Adhikarla, V.K., 2021. Live Spoofing Detection for Automatic Human Activity Recognition Applications. Sensors, 21(2021), p.7339.
[9] Viktor, Huszár. "A blokklánc, a számítógépes látás és a mesterséges intelligencia alkalmazási lehetőségei a kiberhadviselésben." https://tudasportal.uni-nke.hu/xmlui/handle/20.500. 12944/16208 (2021).
[10] Huszár, Viktor. "Distributed Intelligence: Cyber Warfare Application Possibilities of Computer Vision and Artificial Intelligence." Honvédségi Szemle–Hungarian Defence Review 149.1-2. (2021): 4-19.
[11] Huszár, Viktor. "Kiberbiztonság mint a haderőfejlesztés kiemelt területe: a decentralizáció és a blokklánc-technológia lehetőségei a kibertérben." Honvédségi Szemle–Hungarian Defence Review 148.3 (2020): 3-17.
[12] Huszár, Viktor. "Application Possibilities of Decentralization and Blockchain Technology Using Computer Vision and Artificial Intelligence in Defense Management, Military and Police Organizations." HONVÉDSÉGI SZEMLE: A MAGYAR HONVÉDSÉG KÖZPONTI FOLYÓIRATA (2008-) 148.1.-SI (2020): 4-14.
[13] Viktor, Huszár. "A decentralizáció és a blockchain-technológia felhasználási lehetőségei gépi látás és mesterséges intelligencia használatával a katonai szervezetekben." Hadmérnök 14.4 (2019): 179-189.

Contacts

Huszár Viktor Dénes - opv@teqball.com
Adhikarla Vamsi Kiran – vamsi.kiran@fiteq.org

Year / Month	Women's singles	Women's doubles	Mixed doubles
2023/3	-	243	1555
2023/2	-	238	1531
2023/1	-	239	1538
2022/12	-	239	1556
2022/11	-	228	1535
2022/10	-	222	1523
2022/9	-	209	1458
2022/8	-	188	1410
2022/7	-	187	1403
2022/6	-	178	1372
2022/5	-	169	-
2022/4	-	164	-
2022/3	-	143	-
2022/2	-	145	-
2022/1	-	139	-
2021/12	-	1286	-
2021/11	-	1315	-
2021/10	-	1338	-
2021/9	-	1325	-
2021/8	-	1163	-
2021/7	-	992	-
2021/6	-	891	-
2021/5	-	687	-
2021/4	-	628	-
2021/3	-	508	-