Target Detection Label Assignment Method Based on Global Information
With the development of deep learning framework, new object detection algorithms have also been proposed, such as first-stage and two-stage detection models, which have improved the detection speed and solved the problem of object detection at different scales, but they have not yet been well solved...
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| Format: | Article |
| Language: | zho |
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Harbin University of Science and Technology Publications
2022-08-01
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| Series: | Journal of Harbin University of Science and Technology |
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| Online Access: | https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=2114 |
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| _version_ | 1849303615828656128 |
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| author | ZHANG Pei-pei LU Zhen-yu |
| author_facet | ZHANG Pei-pei LU Zhen-yu |
| author_sort | ZHANG Pei-pei |
| collection | DOAJ |
| description | With the development of deep learning framework, new object detection algorithms have also been proposed, such as first-stage and two-stage detection models, which have improved the detection speed and solved the problem of object detection at different scales, but they have not yet been well solved for overlapping, occlusion and other issues. One of the reasons for this problem is that during model training, label assignment is not done well. Aiming at this problem, this paper proposes a target detection label allocation method based on global information, which uses the assignment method to establish a global optimal label allocation mathematical model based on the loss function in the model training stage, and gives the fusion mode of the model with other object detection models, and the role played by the method in the process of object detection. The experimental results show that the detection model of the fusion method is better than that of the model that does not use the method under the complex detection scenarios such as overlapping and occlusion. |
| format | Article |
| id | doaj-art-c65362bfe199442f813d559fef4a0b7b |
| institution | Kabale University |
| issn | 1007-2683 |
| language | zho |
| publishDate | 2022-08-01 |
| publisher | Harbin University of Science and Technology Publications |
| record_format | Article |
| series | Journal of Harbin University of Science and Technology |
| spelling | doaj-art-c65362bfe199442f813d559fef4a0b7b2025-08-20T03:56:03ZzhoHarbin University of Science and Technology PublicationsJournal of Harbin University of Science and Technology1007-26832022-08-012704323810.15938/j.jhust.2022.04.005Target Detection Label Assignment Method Based on Global InformationZHANG Pei-pei0LU Zhen-yu1College of Management , North China University of Science and Technology, Tangshan 063000, ChinaCollege of Management , North China University of Science and Technology, Tangshan 063000, ChinaWith the development of deep learning framework, new object detection algorithms have also been proposed, such as first-stage and two-stage detection models, which have improved the detection speed and solved the problem of object detection at different scales, but they have not yet been well solved for overlapping, occlusion and other issues. One of the reasons for this problem is that during model training, label assignment is not done well. Aiming at this problem, this paper proposes a target detection label allocation method based on global information, which uses the assignment method to establish a global optimal label allocation mathematical model based on the loss function in the model training stage, and gives the fusion mode of the model with other object detection models, and the role played by the method in the process of object detection. The experimental results show that the detection model of the fusion method is better than that of the model that does not use the method under the complex detection scenarios such as overlapping and occlusion.https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=2114object detectionlabel assignmentassign the modeldeep learning |
| spellingShingle | ZHANG Pei-pei LU Zhen-yu Target Detection Label Assignment Method Based on Global Information Journal of Harbin University of Science and Technology object detection label assignment assign the model deep learning |
| title | Target Detection Label Assignment Method Based on Global Information |
| title_full | Target Detection Label Assignment Method Based on Global Information |
| title_fullStr | Target Detection Label Assignment Method Based on Global Information |
| title_full_unstemmed | Target Detection Label Assignment Method Based on Global Information |
| title_short | Target Detection Label Assignment Method Based on Global Information |
| title_sort | target detection label assignment method based on global information |
| topic | object detection label assignment assign the model deep learning |
| url | https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=2114 |
| work_keys_str_mv | AT zhangpeipei targetdetectionlabelassignmentmethodbasedonglobalinformation AT luzhenyu targetdetectionlabelassignmentmethodbasedonglobalinformation |