Face image data in natural scenes is usually distributed in nonlinear high-dimensional space. Therefore, traditional linear feature extraction algorithms are difficult to obtain robust features. Aiming at the above problems, a face recognition algorithm based on nonlinear extraction is proposed. The algorithm introduces the nonlinear feature extraction algorithm into the process of face recognition, pre-processes the face feature matching threshold, fuses the simulated genetic annealing algorithm with the deep belief network, and first optimizes the deep belief network by using the simulated g...
