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

在智慧农业领域,精确识别果蔬种类及定位对提高农业生产效率至关重要。基于卷积神经网络探索CNN图像识别原理及关键技术,构建一个从数据采集、预处理到智能识别的果蔬图像的高质量识别模型,设计并实现了基于卷积神经网络的果蔬识别与定位软件,该软件能高效地从复杂的果蔬外观特征中提取有效信息,智能精准识别果蔬类型及位置信息,能显著提升农业自动化和智能化水平,为提升农作物管理效率和优化生产流程提供高效的工具,对推动智慧农业的发展提供有力技术支撑。

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.