关键词: 深度信念网络, 网络结构, 学习算法, 医学图像

Abstract:

As an important model in Deep Learning（DL）, Deep Belief Network（DBN） has been successfully applied in face recognition, fingerprint recognition, speech recognition, handwriting recognition, medical image analysis and so on. This paper mainly does four aspects of work about deep belief networks. Firstly, this paper discusses the basic principle of depth belief network from two aspects of restricted Boltzmann machine and depth belief network structure and learning process. Secondly, it summarizes the research progress of depth belief network from two aspects of network structure and learning algorithm. In terms of the network structure, it sums up the process from the three aspects： network depth , RBM structure and DBN cascade. In the learning algorithm,  it analyzes the learning process from  basic algorithm, optimization algorithm and fusion method. Thirdly, it summarizes the application of deep belief network in medical image analysis. Fourth, it summarizes the existing problems of DBN.

Key words: Deep Belief Network（DBN）, network structure, learning algorithm, medical image