摘要
深度学习是目前机器学习领域最热门的研究方向,轰动全球的AlphaGo就是用深度学习算法训练的.卷积神经网络是用深度学习算法训练的一种模型,它在计算机视觉领域应用广泛,而且获得了巨大的成功.本文的主要目的有2个:一是帮助读者深入理解卷积神经网络,包括网络结构、核心概念、操作和训练;二是对卷积神经网络的近期研究进展进行综述,重点综述了激活函数、池化、训练及应用4个方面的研究进展.另外,还对其面临的挑战和热点研究方向进行了讨论.本文将为从事相关研究的人员提供很好的帮助.
Deep learning is the most popular research topic in the field of machine learning,AlphaGo which overwhelmingly impacts the world is trained with deep learning algorithms.Convolution neural network(CNN)is a model trained with deep learning algorithm,CNN is widely and successfully applied in computer version.The main purpose of this paper includes two aspects:one is to provide readers with some insights into CNN including its architecture,related concepts,operations and its training;the other is to present a comprehensive survey on research advances of CNN,mainly focusing on 4 aspects:activation functions,pooling,training and applications of CNN.Furthermore,the emerging challenges and hot research topics of CNN are also discussed.This paper can be very helpful to researchers in related field.
出处
《河北大学学报(自然科学版)》
CAS
北大核心
2017年第6期640-651,共12页
Journal of Hebei University(Natural Science Edition)
基金
国家自然科学基金资助项目(71371063)
河北省自然科学基金资助项目(F2017201026)
河北大学自然科学研究计划项目(799207217071)
关键词
机器学习
深度学习
卷积神经网络
计算机视觉
训练算法
machine learning
deep learning
convolutional neural network
computer version
training algorithms