Global channel attention boosted active millimeter wave image object detection
Due to the low discrimination between objects and background texture in active millimeter wave images and the need for security in real time, a global channel attention booster-based method for active millimeter wave image object detection is proposed. In order to improve attention to the global cha...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
National Computer System Engineering Research Institute of China
2024-03-01
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| Series: | Dianzi Jishu Yingyong |
| Subjects: | |
| Online Access: | http://www.chinaaet.com/article/3000164110 |
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| Summary: | Due to the low discrimination between objects and background texture in active millimeter wave images and the need for security in real time, a global channel attention booster-based method for active millimeter wave image object detection is proposed. In order to improve attention to the global channel information of the concealed object and improve detection performance when the concealed object could not be distinguished from the background texture, this method uses YOLOv5s as the carrier and adds global channel attention to the position direction of coordinate attention. And the K-Means ++ clustering method is used to create the anchor box for identifying concealed objects in millimeter wave images. The results demonstrate that both for array image dataset and line sweep image dataset, the detection model enhances the attention of hidden objects feature and improves the detection performance on the basis of meeting the security real-time performance. |
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| ISSN: | 0258-7998 |