Handwritten Character Recognition Based on CUDA and Deep Belief Networks

By combining Compute Unified Device Architecture (CUDA) and Deep Belief Network (DBN), this paper proposes a method to handle the recognition of massive handwritten characters. This method integrates Restricted Boltzmann Machine (RBM) and back propagation neural network to forming a DBN to recognize the characters. Moreover, the concurrent computation of CUDA is made in GPU to achieve the recognition. The results show that the proposed method can significantly improve the speed of recognition on handwritten characters without reducing the accuracy of recognition.