Hybrid intelligent system clonart applied to face recognition

The present work utilizes the framework Clonart (Clonal Adaptive Resonance Theory) that employs many different techniques such as intelligent operators, clonal selection principle, local search, memory antibodies and ART clusterization in order to increase the performance of the algorithm. The approach uses a mechanism similar to the ART 1 network for storing a population of memory antibodies that will be responsible for the acquired knowledge of the algorithm. This characteristic allows the algorithm a self-organization of the antibodies in accordance with the complexity of the database used. A face recognition test case was applied to estimate the performance of this framework with different problem domains.