Artificial intelligence retrieval system for softwood based on feature selection

Wood retrieval is to search the macroscopic and microscopic characteristics observed after wood dissection, and finally obtain the tree species results. The softwood data from the Eyewood website is taken as the research object. Through the organization and analysis of the data, it was found that the order of feature retrieval is different, and the time to obtain accurate retrieval results is different. This illustrates the importance of the order of retrieval features in the retrieval process. This study is based on feature selection algorithm and uses variance analysis method in filtered features to remove irrelevant features; An intelligent retrieval model for softwood was established by sorting features using the size of chi square values. Based on this model, an intelligent retrieval system for softwood was implemented and launched using Python programming language and popular development frameworks and databases( http://woodlab.swfu.edu.cn/ewood-softwood-ai-finder-cn ). • Development of softwood artificial intelligence retrieval system. • This study sorted and analyzed the softwood data through Eyewood website. • Construction of softwood intelligent retrieval system.