摘要
水果自动无损品质检测与分级分类是保障人们健康的重要措施,也间接影响着水果的经济价值。随着计算机技术的飞速发展,以深度学习为代表的人工智能方法在水果品质检测与分级分类领域的研究中取得了一系列重要成果。本文概述了深度学习的背景及常用的深度学习主流算法,然后从水果外部品质检测、内部品质检测、安全品质检测和分级分类等方面综述了近年来深度学习在水果品质检测与分级分类领域的最新研究成果。最后总结了未来深度学习和水果品质检测、分级分类交叉融合研究与应用中的优势,并展望了水果品质检测与分级分类研究融合深度学习的未来发展方向。
Automatic non-destructive quality detection and grading of fruits are important measures to ensure consumer health and indirectly affect the economic value.With the rapid development of computer technology,considerable progress has been made in the application of artificial intelligence methods represented by deep learning in the field of fruit quality detection and grading.In this article,the ABCs and commonly used algorithms of deep learning are summarized.Then,the latest achievements in the application of deep learning in this field are reviewed from the aspects of external quality detection,internal quality detection,safety detection,and quality grading and classification.Finally,it summarizes the advantages in the future research and application of deep learning,fruit quality inspection,grading and classification cross fusion,and looks forward to the future development direction of fruit quality inspection and grading classification research fusion deep learning.
作者
田有文
吴伟
卢时铅
邓寒冰
TIAN Youwen;WU Wei;LU Shiqian;DENG Hanbing(College of Information and Electrical Engineering,Shenyang Agricultral University,Shenyang 110866,China;Research Center of Liaoning Agricultural Informatization Engineering Technology,Shenyang 110866,China)
出处
《食品科学》
EI
CAS
CSCD
北大核心
2021年第19期260-270,共11页
Food Science
基金
国家自然科学基金青年科学基金项目(31601218)
辽宁省教育厅基础研究资助项目(LSNJC201906)。
关键词
深度学习
水果品质检测
水果分级分类
卷积神经网络
图像处理
deep learning
fruit quality detection
fruit grading and classification
convolutional neural network
image processing
