张荣, 李伟平, 莫同. 深度学习研究综述[J]. 信息与控制, 2018, 47(4): 385-397, 410. DOI: 10.13976/j.cnki.xk.2018.8091
引用本文: 张荣, 李伟平, 莫同. 深度学习研究综述[J]. 信息与控制, 2018, 47(4): 385-397, 410. DOI: 10.13976/j.cnki.xk.2018.8091
ZHANG Rong, LI Weiping, MO Tong. Review of Deep Learning[J]. INFORMATION AND CONTROL, 2018, 47(4): 385-397, 410. DOI: 10.13976/j.cnki.xk.2018.8091
Citation: ZHANG Rong, LI Weiping, MO Tong. Review of Deep Learning[J]. INFORMATION AND CONTROL, 2018, 47(4): 385-397, 410. DOI: 10.13976/j.cnki.xk.2018.8091

深度学习研究综述

Review of Deep Learning

  • 摘要: 近年来,中美等国家、谷歌等高科技公司纷纷加大对人工智能的投入,深度学习是目前人工智能的重点研究领域之一,本文对深度学习最新进展及未来研究方向进行了分析和总结.首先概述了三类深度学习基本模型,包括多层感知器、卷积神经网络和循环神经网络.在此基础上,进一步分析了不断涌现出来的新型卷积神经网络和循环神经网络.然后本文总结了深度学习在人工智能众多领域中的应用,包括语音处理、计算机视觉和自然语言处理等.最后探讨了深度学习目前存在的问题并给出了相应的可能解决方法.

     

    Abstract: In recent years, several countries, such as China and the United States, and high-tech companies, such as Google, have increased investment in artificial intelligence. Deep learning is one of the current artificial intelligence research key areas. We analyze and summarize the latest progress and future research directions of deep learning. First, we outline three basic models of deep learning, which are multilayer perceptrons, convolutional neural networks, and recurrent neural networks. On this basis, we further analyze the emerging new models of convolution neural networks and recurrent neural networks. Furthermore, we summarize the applications of deep learning in many areas of artificial intelligence, including speech processing, computer vision, and natural language processing. Finally, we discuss the existing problems of deep learning and provide the corresponding possible solutions.

     

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