A survey on deep learning and its applications

被引：931
作者：
Dong, Shi [1 ,2 ]
Wang, Ping [1 ]
Abbas, Khushnood [1 ]
机构：
[1] Zhoukou Normal Univ, Sch Comp Sci & Technol, Zhoukou 466000, Henan, Peoples R China
[2] Beijing Univ Posts & Telecommun, State key Lab Networking & Switching Technol, Beijing 100876, Peoples R China
来源：
COMPUTER SCIENCE REVIEW | 2021年 / 40卷
关键词：
Deep learning; Stacked auto encoder; Deep belief networks; Deep Boltzmann machine; Convolutional neural network; OBJECT DETECTION; NEURAL-NETWORKS; VEHICLE DETECTION; IMAGE; CLASSIFICATION; SEGMENTATION; ALGORITHM; DROPOUT; SYSTEMS;
D O I：
10.1016/j.cosrev.2021.100379
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
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. (C) 2021 Elsevier Inc. All rights reserved.
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页数：22
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