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基于深度学习的目标检测研究综述

A Review of Object Detection Study Based on Deep Learning

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【作者】 谷永立宗欣欣

【Author】 GU Yongli;ZONG Xinxin;School of Computer Science and Engineering, Anhui University of Science and Technology;

【机构】 安徽理工大学计算机科学与工程学院

【摘要】 目标检测是计算机视觉领域内的热点研究课题,在医疗、监控及航空等领域都有广泛应用。先对目标检测技术的背景进行了介绍,然后从基于锚框的两阶段目标检测算法、基于锚框的单阶段目标检测算法、基于Anchor Free的目标检测算法三个阶段分别进行介绍,同时还介绍了主流的数据集以及主要的性能评价指标。最后叙述了当前目标检测领域存在的挑战,展望了目标检测技术在未来的发展方向。

【Abstract】 Object detection is a hot research topic in the field of computer vision,and it is widely used in medical,monitoring and aviation and other fields.Firstly,this paper introduces the background of object detection technology,and then,the three stages of two stage object detection algorithm based on Anchor frame,the single stage object detection algorithm based on anchor frame and the object detection algorithm based on Anchor Free are introduced respectively.Meanwhile,it also introduces mainstream datasets and main performance evaluation indicators.Finally,the current challenges in the field of object detection are presented,and the object detection technology development direction in future is prospected.

  • 【文献出处】 现代信息科技 ,Modern Information Technology , 编辑部邮箱 ,2022年11期
  • 【分类号】TP391.41;TP18
  • 【下载频次】1865
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