Abstract 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.

Shi Dong

Ping Wang

Khushnood Abbas

Computer Science Review

计算机科学评论旨在通过发布计算机科学和相关领域的研究调查和说明性概述来满足计算机科学界的需求。这些评论面向寻求对最新计算机科学研究的完整和专家概述的普通计算机科学读者。该杂志将发表计算机科学的研究调查和说明性概述。欢迎来自其他领域的文章，只要它们的内容与计算机科学相关。文章应该具有足够的科学兴趣，并有助于促进对一般计算机科学读者正在进行的应用或理论研究的基本理解。每个主题的处理不应该是一个已知结果的目录。重点应放在演示文稿的清晰度和独创性上，每项调查都应增加对所审查主题的洞察力。调查通常包含以下要素：-介绍（包括动机和历史评论）-调查大纲-基本概念、示例和结果（带有证明的草图）-对结果的相关性、与其他结果和应用的关系的评论-开放的问题-相关文献的批判性评论-综合参考书目

The Computer Science Review aims to meet the needs of the computer science community by publishing research surveys and expository overviews in computer science and related fields. These reviews are intended for general computer science readers seeking comprehensive and expert overviews of the latest research. The journal publishes research surveys and expository overviews in computer science and welcomes articles from other fields as long as their content is relevant to computer science. Articles should possess sufficient scientific interest and contribute to a fundamental understanding of ongoing applied or theoretical research for the general computer science reader. Each topic should not merely be a catalog of known results; the focus should be on clarity and originality of presentation, with each survey providing insights into the reviewed topic. Surveys typically include the following elements: - Introduction (including motivation and historical context) - Outline of the survey - Fundamental concepts, examples, and results (with sketches of proofs) - Commentary on the relevance of results and their relationship to other results and applications - Open questions - Critical review of relevant literature - Comprehensive bibliography.

《Computer Science Review》旨在通过发布计算机科学及相关领域的研究调查和说明性概述，满足计算机科学界的需求。这些评论面向寻求对最新计算机科学研究的全面和专家概述的普通计算机科学读者。该杂志将发表计算机科学的研究调查和说明性概述，欢迎来自其他领域的文章，只要其内容与计算机科学相关。文章应具有足够的科学兴趣，并有助于促进对一般计算机科学读者正在进行的应用或理论研究的基本理解。每个主题的处理不应仅仅是已知结果的目录，重点应放在演示文稿的清晰度和独创性上。每项调查都应增加对所审查主题的洞察力。调查通常包含以下要素：- 介绍（包括动机和历史评论）- 调查大纲- 基本概念、示例和结果（带有证明的草图）- 对结果的相关性、与其他结果和应用的关系的评论- 开放的问题- 相关文献的批判性评论- 综合参考书目

Category	Quartile
计算机科学	1
计算机科学, 计算机信息系统	1
计算机科学, 计算机软件工程	1
计算机科学, 计算机理论方法	1

A survey on deep learning and its applications

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Journal Info

Category	Quartile
COMPUTER SCIENCE, THEORY & METHODS	1