基于卷积神经网络的裸体图片识别.doc

文档介绍：基于卷积神经网络的裸体图片识别摘要卷积神经网络是近年来广泛应用于模式识别、图像处理等领域的一种高效识别算法,它具有结构简单、训练参数少和适应性强等特点。本文从卷积神经网络的发展历史开始,详细阐述了卷积神经网络的网络结构、神经元模型和训练算法。在此基础上以卷积神经网络在裸体图片识别和形状识别方面的应用为例,简单介绍了卷积神经网络在工程上的应用,并给出了设计思路和网络结构。关键字: 模型;结构;训练算法;裸体图片识别;形状识别 Abstract Convolution work is an efficient recognition algorithm which is widely used in pattern recognition, image processing and other fields recent has a simple structure, few training parameters and good adaptability and other advantages. In this paper, begin with the history of convolutional works,describes the structure of convolutional work,neuron models and training algorithms in detail. On this basis,uses the applications of convolutional work in face detection and shape recognition as examples, introduces the applications of convolution work in engineering, and gives design ideas work structure. Keywords : Model; Training Algorithm; Advantage; Face detection; Shape recognition 目录摘要..................................................................................................................................................... 1 Abstract ................................................................................................................................................ 2 1 引言............................................................................................................................................... 4 卷积神经网络的发展历史.................................................................................................. 4 2 卷积神经网络................................................................................................................................. 5 网络结构.............................................................................................................................. 5 神经元模型.......................................................................................................................... 7 卷积网络的训练过程................................................................................