基于深度学习的水果品质分级方法综述

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中图分类号：TP183 文献标识码：A文章编号：2096-4706（2025）16-0039-05

Abstract：Fruit quality grading isa key link inagricultural productionand food processing，which directly affects productvalueandmarketcompetitivenes.Inrecent years，with thedeclinecomputer hardwarecostandthe improvement performance，DeepLearning technologyhasdevelopedrapidly，providinganewsolution for fruitqualitygrading.Firstly， this paper introduces the core principle Deep Learing，and compares the characteristics typical algorithms such as Convolutional Neural NetworkandRecurent Neural Network.Secondly，theresearch status fruit quality gradingmethods basedonDeepLeaming athomeandabroad iscomprehensivelyreviewed.Finally，inview the problems existing inthe current fruitquality grading methods，the futureresearch directionand developmentsuggestionsareputforward.Thisstudycan notnlyprovidethoreticalreferencefortheinnovationfruitqualitygradingtechnology，utalsoprovideimportanttechical reference for the development agricultural intelligence.

Keywords： fruit quality grading; Deep Learning; feature extraction; image processing

0 引言

我国地处寒、温、热三带，适宜不同品种水果的种植。（剩余10782字）