Target Recognition Using of PCNN Model Based on Grid Search Method

Abstract

To improve the accuracy of face recognition using pulse coupled neural network（PCNN） model and save the problem that the parameters of PCNN model must be set with experience, the PCNN model based on pulse intensity (QD-PCNN) and the improved grid search method are proposed. In the QD-PCNN, pulse intensity can make the outputs of the model more accurate. When the improved grid search method is used to find the suitable parameters, the parameters are searched in a large space firstly, and then searched accurately around the parameters we have found according to the objects which are to be recognized. In the experimental process, the parameters obtained through improved grid search method is applied to QD-PCNN model to recognize faces, and the results show the efficiency of this method.