基于深度学习的温室鲜枣成熟度检测模型研究  

Study on the Maturity Detection Model of Fresh Dates in Greenhouse based on Deep Learning

作　　者：尹丽华 YIN Lihua(Shanxi Institute of Engineering and Technology,Yangquan,Shanxi 045000)

机构地区：[1]山西工程技术学院,山西阳泉045000

出　　处：《现代农业研究》2024年第1期105-107,共3页Modern Agriculture Research

基　　金：山西省基础研究计划自由探索类青年科学研究项目“温室鲜枣采摘视觉检测模型及末端执行器设计研究”(项目编号:202103021223145)。

摘　　要：温室种植已成为现代果蔬生产的主要方式之一,而鲜枣作为重要的经济作物之一,在温室中的种植面积也越来越大。然而,由于鲜枣的成熟度难以准确地判断,导致其产量和品质存在较大的波动,影响了农民的生产效益和市场竞争力。因此,研究一种高效准确的鲜枣成熟度检测方法具有重要的现实意义。目前,基于传统图像处理技术的成熟度检测方法已经逐渐无法满足现代农业的需求,而深度学习技术在图像识别领域取得了巨大的成功,为鲜枣成熟度检测提供了新的思路和方法。本文旨在设计并实现一种基于深度学习的温室鲜枣成熟度检测模型,以提高鲜枣生产的效率和质量,促进农业现代化的发展。Greenhouse planting has become one of the main ways of modern fruit and vegetable production,and fresh jujube as one of the important cash crops,in the greenhouse planting area is getting bigger and bigger.However,because the maturity of fresh jujube is difficult to accurately judge,the yield and quality fluctuate greatly,which affects the production efficiency and market competitiveness of farmers.Therefore,it is of great practical significance to study an efficient and accurate method of fresh jujube maturity.At present,the maturity detection method based on traditional image processing technology has been unable to meet the needs of modern agriculture,and deep learning technology has achieved great success in the field of image recognition,which provides new ideas and methods for the maturity detection of fresh dates.This paper aims to design and implement a deep learning-based maturity detection model of greenhouse fresh jujube to improve the efficiency and quality of fresh jujube production and promote the development of agricultural modernization.

关 键 词：深度学习 温室鲜枣成熟度 检测模型 

分 类 号：Q141[生物学—生态学]