Design and implementation of pest identification system based on deep learning
Designing a deep learning based pest identification system,and completes basic functions such as system interface design and implementation,back-end system design and implementation,recognition algorithm implementation and other basic functions.This system uses the design pattern of separation of front and back ends in the system architecture,which mainly uses HTML,Flask,PyTorch and other components.In detail,HTML is used to implement front-end services,Python+Flask is used to provide back-end services,and PyTorch is used to implement the recognition algorithm.The test results show that this system can basically meet the needs of pest identification.At the same time,on the self-built pest identification data set,the system's identifi-cation accuracy can reach 90.052%.
deep learningfront-end and back-end separationpest identification system
NETL
NSTL
万方数据
