说明：  《基于多特征融合的稻叶病图像识别系统》 基于机器学习和深度学习算法开发了一个稻叶病图像识别系统,基于颜色特征分割提取稻叶病图像病斑,提取颜色、形状、纹理等多个病斑图像特征维度,基于MCCA多视图典型相关分析进行特征融合得到集成特征,基于CNN、SVM进行稻叶病图像分类,进行了多个分类器对比实验,提高了稻叶病识别准确率和速度;校重点大学生科创基金项目,项目获第十一届“挑战杯”校大学生课外学术科技作品竞赛三等奖。
(The Image Recognition System of Rice Leaf Disease Based on Multi feature Fusion has developed a rice leaf disease image recognition system based on machine learning and deep learning algorithms. It extracts the disease spots of rice leaf disease image based on color feature segmentation, extracts the feature dimensions of multiple disease spots such as color, shape, texture, etc., conducts feature fusion based on MCCA multi view canonical correlation analysis to obtain integrated features, classifies rice leaf disease images based on CNN and SVM, and conducts comparative experiments on multiple classifiers, which improves the accuracy and speed of rice leaf disease recognition; The key university student science and innovation fund project won the third prize in the 11th "Challenge Cup" extracurricular academic and technological works competition for university students.)