计算机视觉下的果实目标检测算法综述

基于计算机视觉的果实目标检测识别是目标检测、计算机视觉、农业机器人等多学科的重要交叉研究课题，在智慧农业、农业现代化、自动采摘机器人等领域，具有重要的理论研究意义和实际应用价值。随着深度学习在图像处理领域中广泛应用并取得良好效果，计算机视觉技术结合深度学习方法的果实目标检测识别算法逐渐成为主流。本文介绍基于计算机视觉的果实目标检测识别的任务、难点和发展现状，以及2类基于深度学习方法的果实目标检测识别算法，最后介绍用于算法模型训练学习的公开数据集与评价模型性能的评价指标，且对当前果实目标检测识别存在的问题和未来可能的发展方向进行讨论。

Survey of Fruit Object Detection Algorithms in Computer Vision

Fruit target detection and recognition based on computer vision is an important cross-disciplinary research topic of target detection, computer vision, agricultural robots, etc. It has important theoretical research significance and practical application value in the fields of smart agriculture, agricultural modernization, and automatic picking robots. As deep learning is widely used in the field of image processing and has achieved good results, fruit target detection and recognition algorithms combining computer vision technology with deep learning methods gradually become the mainstream. This article introduces the tasks, difficulties and development status of fruit target detection and recognition based on computer vision, as well as two types of fruit target detection and recognition algorithms based on deep learning methods. Finally, the public data set used for the training and learning of the algorithm model and the evaluation index for evaluating the performance of the model are introduced, and the current problems in the detection and recognition of fruit targets and the possible future development directions are discussed.