A survey on deep learning and its applications

被引:805
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
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.
引用
收藏
页数:22
相关论文
共 202 条
  • [1] ACKLEY DH, 1985, COGNITIVE SCI, V9, P147
  • [2] Self-adaptive SUM-CNN neural system for dynamic object detection in normal and complex scenarios
    Alberto Ramirez-Quintana, Juan
    Ignacio Chacon-Murguia, Mario
    [J]. PATTERN RECOGNITION, 2015, 48 (04) : 1137 - 1149
  • [3] Moving Objects Segmentation Based on DeepSphere in Video Surveillance
    Ammar, Sirine
    Bouwmans, Thierry
    Zaghden, Nizar
    Neji, Mahmoud
    [J]. ADVANCES IN VISUAL COMPUTING, ISVC 2019, PT II, 2019, 11845 : 307 - 319
  • [4] [Anonymous], 2017, CVPR
  • [5] [Anonymous], 2009, Cambridge University Press, DOI DOI 10.1017/CBO9780511815867
  • [6] [Anonymous], 2014, P 8 INT WORKSH SEM E
  • [7] [Anonymous], 1993, AI TUMULTUOUS HIST S
  • [8] Deep learning
    LeCun, Yann
    Bengio, Yoshua
    Hinton, Geoffrey
    [J]. NATURE, 2015, 521 (7553) : 436 - 444
  • [9] [Anonymous], 2015, ARXIV PREPRINT ARXIV
  • [10] [Anonymous], 2016, P NIPS