图像识别的常用方法有：贝叶斯分类法、模板匹配法、核方法、集成学习方法、

Common methods of image recognition are: Bayesian classification, template matching, kernel method, integrated learning method, artificial neural network method, etc. <br>With the development of pattern recognition and machine learning, some new ideas such as sparse coding, local receptive fields, and hierarchical processing of visual information have been introduced into the research of feature extraction, and some methods such as neural network-based image recognition technology Has made periodic progress. Since 2006, due to the introduction of deep learning, deep learning methods have made new progress in the field of image recognition.

图像识别的常用方法有：贝叶斯分类法、模板匹配法、核方法、集成学习方法、人工神经网络法等等。<br>随着模式识别和机器学习的发展，一些新的思想如稀疏编码、局部感受野、视觉信息的层次式处理等被引入到了特征提取的研究中, 而一些方法如基于神经网络的图像识别技术取得了阶段性的进展。从 2006 年开始，由于深度学习的提出，深度学习的方法在图像识别领域取得了新的进展。

The common methods of image recognition include Bayesian classification, template matching, kernel method, integrated learning method, artificial neural network method and so on.<br>With the development of pattern recognition and machine learning, some new ideas, such as sparse coding, local receptive field, hierarchical processing of visual information, have been introduced into the research of feature extraction, while some methods, such as image recognition technology based on neural network, have made phased progress. Since 2006, the deep learning method has made new progress in the field of image recognition.<br>