Key points are not available for this paper at this time.
Presents a feature recognition network for pattern recognition that learns the patterns by remembering their different segments. The base algorithm for this network is a Boolean net algorithm that the authors developed during past research. Simulation results show that the network can recognize patterns after significant noise, deformation, translation and even scaling. The network is compared to existing popular networks used for the same purpose, especially the Neocognitron. The network is also analyzed as regards to interconnection complexity and information storage/retrieval.>
Hussain et al. (Sat,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: