Double recurrent interaction V1V2V4 based neural architecture for color natural scene boundary detection and surface perception
Bio-inspired neural architecture for natural scene boundary detection. Double feedback among V1, V2 and V4 cortical areas and chromatic diffusion. Results quantified using F-measure from the Berkeley segmentation benchmark. Parallel implementations on GPU: CUDA(R) and Matlab(R). Neural architecture performance and results compatible with real applications.
boundary detection gpu neural networks color image processing bio-inspired models cuda