卷积神经网络架构及其应用的研究

Research on Architectures and Applications of Convolutional Neural Network

本文首先介绍卷积神经网络深度模型的发展历程,其次对其的内部组成结构所对应的各项操作(卷积、池化)进行了详细的阐述分析,最后较全面地分析卷积神经网络在语音识别、表情检测、遥感图像分类及其他领域的具体应用。通过总结研究卷积神经网络技术热点问题,研究人员能够从中提出有用的意见同时发掘出更好的改进方法。

This article first introduces the development of convolution neural network depth model.Secondly,the various operations(convolution and pooling)corresponding to its internal composition are elaborated and analyzed in detail.Finally,a more comprehensive analysis of convolution neural network in speech recognition,facial expression detection,remote sensing image classification and other specific applications.By summarizing the hot issues in convolution neural network technology,researchers can come up with useful ideas and discover better methods to improve it.