A laboratórium munkatársai által készített publikációk, előadások válogatott listája. A munkatársak által készített további publikációk az MTMT adatbázisban név alapján kereshetők.

Alaya, K. B., & Czúni, L. (2021). Stochastic Modeling of Trees in Forest Environments. IEEE Access, 9, 69143-69156.

Nagy, A. M., Rashad, M., & Czúni, L. (2021). Active multiview recognition with hidden Markov temporal support. Signal, Image and Video Processing, 15(2), 315-322.

Czúni, L., & Rashad, M. (2018). Lightweight Active Object Retrieval with Weak Classifiers. Sensors, 18(3), 801.

Szakonyi, B., Lőrincz, T., Lipovits, Á., & Vassányi, I. (2018). An Expert System Framework for Lifestyle Counselling. eTELEMED 2018, 100.

Czúni, L., & Rashad, M. (2017). The use of IMUs for video object retrieval in lightweight devices. Journal of Visual Communication and Image Representation, 48, 30-42.

Czúni, L., & Rashad, M. (2017, September). The Fusion of Optical and Orientation Information in a Markovian Framework for 3D Object Retrieval. In International Conference on Image Analysis and Processing (pp. 26-36). Springer, Cham.

Czúni, L., & Varga, P. Z. (2017). Time Domain Audio Features for Chainsaw Noise Detection Using WSNs. IEEE Sensors Journal, 17(9), 2917-2924.

Seress, G., Lipovits, Á., Bókony, V., & Czúni, L. (2014). Quantifying the urban gradient: a practical method for broad measurements. Landscape and Urban Planning, 131, 42-50.

Borbély, B. J., Kincses, Z., Vörösházi, Z., Nagy, Z., & Szolgay, P. (2014). A modular test platform for real-time measurement and analysis of myoelectric signals for improved prosthesis control. 14th International Workshop on Cellular Nanoscale Networks and their Applications - CNNA 2014, Notre Dame, USA

Czúni, L., Kiss, P. J., Lipovits, Á., & Gál, M. (2014, October). Lightweight mobile object recognition. In Image Processing (ICIP), 2014 IEEE International Conference on (pp. 3426-3428). IEEE.

Cho, D., Kim, H. M., Czúni, L., & Császár, G. (2010). Apparatus and method for super-resolution enhancement processing, U.S. Patent No. 7,715,658. Washington, DC: U.S. Patent and Trademark Office.

Vörösházi, Z., Nagy, Z., & Szolgay, P. (2009). FPGA-based real time, multichannel emulated-digital retina model implementation. EURASIP Journal on Advances in Signal Processing, 2009(1), 749838.

Czúni, L., & Szirányi, T. (2001). Motion segmentation and tracking with edge relaxation and optimization using fully parallel methods in the cellular nonlinear network architecture. Real-Time Imaging, 7(1), 77-95.

Szirányi, T., Zerubia, J., Czúni, L., Geldreich, D., & Kato, Z. (2000). Image segmentation using Markov random field model in fully parallel cellular network architectures. Real-Time Imaging, 6(3), 195-211.