深度学习
计算机科学
人工智能
深信不疑网络
卷积神经网络
限制玻尔兹曼机
人工神经网络
边疆
玻尔兹曼机
机器学习
历史
考古
作者
Shi Dong,Ping Wang,Khushnood Abbas
标识
DOI:10.1016/j.cosrev.2021.100379
摘要
Deep learning, a branch of machine learning, is a frontier for artificial intelligence, aiming to be closer to its primary goal—artificial intelligence. This paper mainly adopts the summary and the induction methods of deep learning. Firstly, it introduces the global development and the current situation of deep learning. Secondly, it describes the structural principle, the characteristics, and some kinds of classic models of deep learning, such as stacked auto encoder, deep belief network, deep Boltzmann machine, and convolutional neural network. Thirdly, it presents the latest developments and applications of deep learning in many fields such as speech processing, computer vision, natural language processing, and medical applications. Finally, it puts forward the problems and the future research directions of deep learning.
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