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基于深度学习的无锚框目标检测算法综述

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近年来,基于深度学习的无锚框目标检测算法备受关注.为了深入理解无锚框检测算法,对比分析了基于深度学习的无锚框检测算法的原理机制、网络结构、核心特性以及优缺点,归纳总结了无锚框检测算法的核心技术,并在同一数据集上通过性能实验研究上述算法的性能,总结提出基于深度学习的目标检测算法未来的研究方向.
Overview of Anchor-Free Object Detection Algorithms Based on Depth Learning
In recent years,target detection algorithm based on deep learning has attracted much attention.In order to deeply under-stand the typical anchor-free object detection algorithms,the principle mechanism,network structure,core characteristics,advantages and disadvantages of seven anchor-free object detection algorithms based on deep learning were compared and analyzed.The perform-ance of the above algorithms was experimentally studied.On this basis,the main characteristics of the anchor-free object detection algo-rithm were summarized,and the research direction of the anchor-free object detection algorithm was pointed out.

anchor-free object detection algorithmdeep learningalgorithm comparison

高海涛、朱超涵、张天棋、郝飞、茅新宇

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南京工程学院机械工程学院,江苏南京 211167

无锚框目标检测算法 深度学习 算法比较

国家自然科学基金青年科学基金江苏省研究生实践创新计划项目江苏省研究生实践创新计划项目江苏省现代农机装备与技术示范推广项目

51705238SJCX_0916SJCX23_1173NJ2021-58

2024

机床与液压
中国机械工程学会 广州机械科学研究院有限公司

机床与液压

CSTPCD北大核心
影响因子:0.32
ISSN:1001-3881
年,卷(期):2024.52(1)
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