A neural architecture for fully data driven edge-preserving image restoration
Integrated Computer-Aided Engineering
Neural Computation
Brightness perception, dynamic range and noise: a unifying model for adaptive image sensors
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
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The amount of computation required to solve many early vision problems is prodigious, and so it has long been thought that systems that operate in a reasonable amount of time will only become feasible when parallel systems become available. Such systems now exist in digital form, but they are large and expensive. Simple analog networks can perform interesting computations, as has been known for a long time. We have reached the point where it is feasible to experiment with implementation of these ideas in VLSI form, particularly if we focus on networks composed of locally interconnected passive elements, linear amplifiers, and simple non-linear components.