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: 1996 fourth IEEE international workshop on Cellular Neural Networks and their applications proceedings. CNNA-96. Seville, 1996..
Distance preserving 1D turing-wave models via CNN, implementation of complex-valued CNN and solving a simple inverse pattern problem (detection)
Real-time adaptive control of robot manipulators using Cellular Neural Networks. ( Research report of the Analogical and Neural Computing Laboratory DNS-10-1996.)
Implementation of large-neighborhood nonlinear templates on the CNN universal machine. ( Research report of the Analogical and Neural Computing Laboratory, DNS-7-1996.)
CNN model of the feature-linked synchronized activities in the visual thalamo-cortical system.(Research report of the Neuromorphic Information Technology Graduate Center. NIT-2-1966.)