卷积神经网络及其研究进展
发布时间:2018-10-09 12:36
【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.
[Abstract]:Deep learning is the most popular research direction in the field of machine learning at present. The global AlphaGo is trained with depth learning algorithm. Convolution neural network is a kind of model trained by deep learning algorithm. It is widely used in the field of computer vision and has achieved great success. The main purpose of this paper is to help readers understand convolutional neural networks deeply, including network structure, core concepts, operation and training. Research progress in pooling, training and application. In addition, the challenges and hot research directions are also discussed. This article will provide the very good help for the personnel engaged in the related research.
【作者单位】: 河北大学数学与信息科学学院河北省机器学习与计算智能重点实验室;中国气象局气象干部培训学院河北分院;
【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)
【分类号】:TP183
,
本文编号:2259358
[Abstract]:Deep learning is the most popular research direction in the field of machine learning at present. The global AlphaGo is trained with depth learning algorithm. Convolution neural network is a kind of model trained by deep learning algorithm. It is widely used in the field of computer vision and has achieved great success. The main purpose of this paper is to help readers understand convolutional neural networks deeply, including network structure, core concepts, operation and training. Research progress in pooling, training and application. In addition, the challenges and hot research directions are also discussed. This article will provide the very good help for the personnel engaged in the related research.
【作者单位】: 河北大学数学与信息科学学院河北省机器学习与计算智能重点实验室;中国气象局气象干部培训学院河北分院;
【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)
【分类号】:TP183
,
本文编号:2259358
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