Review of Object Detection Algorithm Improvement in Deep Learning

被引:0
|
作者
Yang, Feng [1 ]
Ding, Zhitong [2 ]
Xing, Mengmeng [3 ]
Ding, Bo [2 ]
机构
[1] Assets and Equipment Department, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan,250013, China
[2] School of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan,255424, China
[3] Department of Medicine and Engineering, China Rehabilitation Research Center, Beijing,100071, China
关键词
Object detection;
D O I
10.3778/j.issn.1002-8331.2209-0312
中图分类号
学科分类号
摘要
Object detection is currently a research hotspot in the field of computer vision. With the development of deep learning, object detection algorithms based on deep learning are increasingly applied and their performance is constantly improved. This paper summarizes the latest research progress of object detection methods based on deep learning by summarizing common problems encountered in the process of object detection and corresponding improvement methods. This paper focuses on two types of object detection algorithms based on deep learning. In addition, the latest improvement ideas of target detection algorithms are summarized from the aspects of attention mechanism, lightweight network, multiscale detection. Finally, in view of the current problems in the field of target detection, the future development trend is prospected. And the feasible solution is put forward in order to provide reference ideas and directions for the follow-up research work in this field. © 2023 Journal of Computer Engineering and Applications Beijing Co., Ltd.; Science Press. All rights reserved.
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页码:1 / 15
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