Artificial intelligence (AI) has entered a new period of vigorous development. This round of AI topsy is driven by three engines, namely the depth of learning (DL), big data and massively parallel computing, with DL as the core. This article reviews from a historical perspective the basic situation of the round "deep neural networks renaissance", then summarizes the four common depth models: deep belief network (DBN), depth from network coding (DAN), deep convolutional neural networks (DCNN) and long short term memory recurrent neural network LSTM-RNN. After that, this paper briefly introduces the application effects of deep learning in speech recognition and computer vision. In order to facilitate the application of DL, it also introduces several commonly used deep learning platforms. Finally, the enlightenment and reform of deep learning are commented, and the open problems and development trend in this field are discussed.

multilayer neural networks  /  DBN  /  DAN  /  DCNN  /  LSTM-RNN  /  speech recognition  /  computer vision