软件导刊2019，Vol.18Issue(1)：5-8,4.DOI:10.11907/rjdk.181736
基于卷积神经网络的中国绘画图像分类
Chinese Painting Image Classification Based on Convolution Neural Network
摘要
Abstract
The classification of painting images facilitates the management and use of paintings.Different from traditional image classification, features such as artificial extraction of shapes and colors are required.Classification of painting images requires a more professional knowledge background, which also makes the process of manually extracting features increasingly complicated.Based on this, a Chinese painting classification method based on convolutional neural network is proposed.Based on this, it combines the advantages of two activation functions including SoftSign and ReLU to construct a new activation function.Experimental results show that the convolutional neural network constructed based on the improved activation function can effectively improve the classification accuracy.关键词
深度学习/卷积神经网络/中国绘画/激活函数/图像分类Key words
deep learning/convolution neural network/Chinese painting/activation function/image classification分类
信息技术与安全科学引用本文复制引用
杨冰,陈浩月,王小华,姚金良..基于卷积神经网络的中国绘画图像分类[J].软件导刊,2019,18(1):5-8,4.基金项目
国家自然科学基金项目(61402143) （61402143）
