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Frontiers and advances of deep learning-based fruit and vegetable image analysis

文献类型：期刊论文

作者Ma, Jinlin2,3; Wan, Yuetong2; Min, Weiqing1,4; Ma, Ziping2; Tan, Lidao2; Jiang, Shuqiang1,4
刊名COMPUTERS AND ELECTRONICS IN AGRICULTURE
出版日期2026-02-01
卷号241页码:22
关键词Deep learning Fruit and vegetable image analysis Quality grading Yield estimation
ISSN号0168-1699
DOI10.1016/j.compag.2025.111256
英文摘要Deep learning has achieved promising performance for fruit and vegetable image analysis, by possessing strong representation power, and providing resilient generalization and broad transferability on large-scale data for classification, detection, and segmentation tasks, which is indispensable role in optimizing agricultural practices. This comprehensive survey reviews over 270 recent studies, offering a deep exploration of the key techniques and strategies, fundamental properties, and advancements and future directions according to different categories of deep learning methods for fruit and vegetable image analysis. Furthermore, this paper outlines the novelty and concept of fruit and vegetable image analysis, summarizes publicly available datasets, evaluation metrics, and discusses successful applications in disease detection, quality grading, yield estimation, localization, and multiple application integration. The survey emphasizes the need for processing large-scale datasets and exploring the potential of efficient deep learning for enhancing real-time applications and specific tasks. By comprehensively comparing and analyzing the fundamental attributes of the fruit and vegetable image analysis methods from a fresh perspective, this survey reveals the commonalities and disparities of divert techniques and guides researchers and practitioners toward developing more efficient and accurate solutions.
资助项目National Natural Science Foundation of China[62462001] ; National Natural Science Foundation of China[62562002] ; National Natural Science Foundation of China[U19B2040] ; Natural Science Foundation of Ningxia[2025AAC020007] ; Natural Science Foundation of Ningxia[2024AAC03147] ; Innovation Team of Image and Intelligent Information Processing of National Ethnic Affairs Commission
WOS研究方向Agriculture ; Computer Science
语种英语
WOS记录号WOS:001629707500001
出版者ELSEVIER SCI LTD
源URL[http://119.78.100.204/handle/2XEOYT63/42967]  
专题中国科学院计算技术研究所
通讯作者Ma, Jinlin
作者单位1.Chinese Acad Sci, Key Lab Intelligent Informat Proc, Inst Comp Technol, Beijing 100190, Peoples R China
2.North Minzu Univ, Sch Comp Sci & Engn, Yinchuan 750021, Peoples R China
3.State Ethn Affairs Commiss, Key Lab Intelligent Informat Proc Image & Graph, Yinchuan, Peoples R China
4.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
推荐引用方式
GB/T 7714		 Ma, Jinlin,Wan, Yuetong,Min, Weiqing,et al. Frontiers and advances of deep learning-based fruit and vegetable image analysis[J]. COMPUTERS AND ELECTRONICS IN AGRICULTURE,2026,241:22.
APA Ma, Jinlin,Wan, Yuetong,Min, Weiqing,Ma, Ziping,Tan, Lidao,&Jiang, Shuqiang.(2026).Frontiers and advances of deep learning-based fruit and vegetable image analysis.COMPUTERS AND ELECTRONICS IN AGRICULTURE,241,22.
MLA Ma, Jinlin,et al."Frontiers and advances of deep learning-based fruit and vegetable image analysis".COMPUTERS AND ELECTRONICS IN AGRICULTURE 241(2026):22.

入库方式： OAI收割

来源：计算技术研究所

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