Department of Tradition Chinese Painting, Xi'an Academy of Fine Arts, Xian, Shaanxi 710000, China.
Comput Intell Neurosci. 2022 Aug 30;2022:4520913. doi: 10.1155/2022/4520913. eCollection 2022.
People's appreciation needs of Chinese paintings have gradually increased. The research on automatic classification and recognition of Chinese painting artistic style and its authors have great practical value. This study presents a Chinese painting classification algorithm with higher classification accuracy and better robustness. Using a convolutional neural network (CNN) to extract the features of Chinese painting, the image features of Chinese painting are extracted by fine-tuning the pretrained VGG-F model. The mutual information theory is introduced into embedded machine learning, so that the embedded principle is affected by feature selection and feature importance. An embedded classification algorithm based on mutual information is proposed, and Chinese painting is classified.
人们对中国画的欣赏需求逐渐增加。对中国画艺术风格及其作者的自动分类和识别的研究具有很大的实用价值。本研究提出了一种具有更高分类精度和更好鲁棒性的中国画分类算法。使用卷积神经网络（CNN）提取中国画的特征，通过微调预训练的 VGG-F 模型提取中国画的图像特征。将互信息理论引入嵌入式机器学习中，使嵌入式原理受到特征选择和特征重要性的影响。提出了一种基于互信息的嵌入式分类算法，并对中国画进行了分类。
