现代信息科技2024，Vol.8Issue(16)：98-101,106,5.DOI:10.19850/j.cnki.2096-4706.2024.16.021
基于卷积神经网络的果蔬识别与定位软件的设计与实现
Design and Implementation of Fruit and Vegetable Recognition and Localization Software Based on Convolutional Neural Networks
摘要
Abstract
In the field of smart agriculture,accurately identifying the types and locations of fruits and vegetables is crucial for improving agricultural production efficiency.This paper explores the principles and key technologies of image recognition based on Convolutional Neural Networks(CNN),and constructs a high-quality recognition model for fruit and vegetable images that encompasses data collection,preprocessing,and intelligent recognition.A software based on Convolutional Neural Networks for the recognition and location of fruits and vegetables is designed and implemented.This software can efficiently extract useful information from complex appearances of fruits and vegetables,intelligently and accurately identify their types and location information,significantly enhancing the level of agricultural automation and intelligence.It provides a powerful tool for improving crop management efficiency and optimizing production processes,offering strong technical support for the advancement of smart agriculture.关键词
卷积神经网络/软件开发/果蔬图像识别/智慧农业Key words
Convolutional Neural Networks/software development/fruit and vegetable image recognition/smart agriculture分类
信息技术与安全科学引用本文复制引用
何伟..基于卷积神经网络的果蔬识别与定位软件的设计与实现[J].现代信息科技,2024,8(16):98-101,106,5.基金项目
江苏高校"青蓝工程"中青年学术带头人项目(2022) （2022）
