YOLOv3-A: a traffic sign detection network based on attention mechanism
To solve the problem that the existing YOLOv3 algorithm had more false detections and missed detections for traffic sign detection task with small target problems and complex background, based on the YOLOv3, a channel attention method for target detection and a spatial attention method based on sema...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Department of Journal on Communications
2021-01-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2021031/ |
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| _version_ | 1841539305902702592 |
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| author | Fan GUO Yongxiang ZHANG Jin TANG Weiqing LI |
| author_facet | Fan GUO Yongxiang ZHANG Jin TANG Weiqing LI |
| author_sort | Fan GUO |
| collection | DOAJ |
| description | To solve the problem that the existing YOLOv3 algorithm had more false detections and missed detections for traffic sign detection task with small target problems and complex background, based on the YOLOv3, a channel attention method for target detection and a spatial attention method based on semantic segmentation guidance were proposed to form the YOLOv3-A (attention) algorithm.The detection features in the channel and spatial dimensions were recalibrated, allowing the network to focus and enhance the effective features, and suppress interference features, which greatly improved the detection performance.Experiments on the TT100K traffic sign data set show that the algorithm improves the detection performance of small targets, and the accuracy and recall rate of the YOLOv3 are improved by 1.9% and 2.8% respectively. |
| format | Article |
| id | doaj-art-bba255afb2f54b6b81e6e4931fc0f9ad |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2021-01-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-bba255afb2f54b6b81e6e4931fc0f9ad2025-01-14T07:21:30ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2021-01-0142879959739738YOLOv3-A: a traffic sign detection network based on attention mechanismFan GUOYongxiang ZHANGJin TANGWeiqing LITo solve the problem that the existing YOLOv3 algorithm had more false detections and missed detections for traffic sign detection task with small target problems and complex background, based on the YOLOv3, a channel attention method for target detection and a spatial attention method based on semantic segmentation guidance were proposed to form the YOLOv3-A (attention) algorithm.The detection features in the channel and spatial dimensions were recalibrated, allowing the network to focus and enhance the effective features, and suppress interference features, which greatly improved the detection performance.Experiments on the TT100K traffic sign data set show that the algorithm improves the detection performance of small targets, and the accuracy and recall rate of the YOLOv3 are improved by 1.9% and 2.8% respectively.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2021031/traffic sign detectionsmall target detectionattention mechanismsemantic segmentation |
| spellingShingle | Fan GUO Yongxiang ZHANG Jin TANG Weiqing LI YOLOv3-A: a traffic sign detection network based on attention mechanism Tongxin xuebao traffic sign detection small target detection attention mechanism semantic segmentation |
| title | YOLOv3-A: a traffic sign detection network based on attention mechanism |
| title_full | YOLOv3-A: a traffic sign detection network based on attention mechanism |
| title_fullStr | YOLOv3-A: a traffic sign detection network based on attention mechanism |
| title_full_unstemmed | YOLOv3-A: a traffic sign detection network based on attention mechanism |
| title_short | YOLOv3-A: a traffic sign detection network based on attention mechanism |
| title_sort | yolov3 a a traffic sign detection network based on attention mechanism |
| topic | traffic sign detection small target detection attention mechanism semantic segmentation |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2021031/ |
| work_keys_str_mv | AT fanguo yolov3aatrafficsigndetectionnetworkbasedonattentionmechanism AT yongxiangzhang yolov3aatrafficsigndetectionnetworkbasedonattentionmechanism AT jintang yolov3aatrafficsigndetectionnetworkbasedonattentionmechanism AT weiqingli yolov3aatrafficsigndetectionnetworkbasedonattentionmechanism |