A Novel CNN Template Design Method Based on GIM

摘要

In this paper, a kind of relation between CNN (cellular neural network) and GIM (Gibbs image model) is noted. Based on this relation, a new approach for CNN's template design is proposed, this approach is valid to many questions that could be processed with GIM, such as segmentation, edge detection and restoration. We also discuss the learning algorithm and hardware annealing jointed with the new approach. Simulations of some examples are shown in order to validate effectiveness of new approach.