Computational Optical Sensing and Processing Laboratory
The main research challenge of our laboratory is to derive precise abstract information or decisions from large complex noisy topological data sets captured by one or multiple optical sensors. We apply special optical arrangements such as different holographic setups and fluorescent illuminations for microscopic imaging, or multi-spectral camera-based patient monitoring systems or wide-angle multi-camera systems in monitoring. The heavy computational load is handled by many-core processor arrays, such as GPUs in desktop applications or embedded low-power systems.
Publication date
1996
In: ISANN'95. 1995 international symposium on artificial neural networks. Taiwan, 1995..
Improving the noisy feature detection capability of feedforward Cellular Neural Networks by introducing don't- care template elements
In: Engineering of intelligent systems. 14th international conference on industrial and engineering applications of artificial intelligence and expert systems, IEA/AIE. Proceedings. Budapest, 2001. (Lecture notes in artificial intelligence 2070.).
Short circuit detection on printed circuit boards during the manufacturing process by using an analogic CNN algorithm
Real-time adaptive control of robot manipulators using Cellular Neural Networks. ( Research report of the Analogical and Neural Computing Laboratory DNS-10-1996.)