SAR ship detection based on improved YOLOv5 and BiFPN
Synthetic aperture radar (SAR) is an advanced microwave sensor widely used in ocean monitoring, whose operation is not affected by light and weather. Ship targets in SAR images contain characteristically unclear contour information, a complex background, and display strong scattering. Ship detection...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Elsevier
2024-02-01
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| Series: | ICT Express |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S240595952300036X |
| _version_ | 1827349049721749504 |
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| author | Chushi Yu Yoan Shin |
| author_facet | Chushi Yu Yoan Shin |
| author_sort | Chushi Yu |
| collection | DOAJ |
| description | Synthetic aperture radar (SAR) is an advanced microwave sensor widely used in ocean monitoring, whose operation is not affected by light and weather. Ship targets in SAR images contain characteristically unclear contour information, a complex background, and display strong scattering. Ship detection algorithms based on convolutional neural networks achieved good results, albeit with many missed and false detections. To address this issue, we propose an improved scheme based on YOLOv5, that combines coordinate attention blocks and uses a bidirectional feature pyramid network for better feature fusion. Experimental results obtained with SAR images datasets demonstrate the effectiveness and applicability of the proposed model when applied for ship detection in SAR images. Compared to the original YOLOv5, the detection accuracy of the proposed method was increased from 81.28% to 88.27%, and the mean average precision was increased from 92.57% to 95.02%, which showed significant performance improvement by the proposed method in terms of detection accuracy and speed. |
| first_indexed | 2024-03-08T00:23:26Z |
| format | Article |
| id | doaj.art-f3345f9b68914952ac1482465908a1ff |
| institution | Directory Open Access Journal |
| issn | 2405-9595 |
| language | English |
| last_indexed | 2024-03-08T00:23:26Z |
| publishDate | 2024-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | ICT Express |
| spelling | doaj.art-f3345f9b68914952ac1482465908a1ff2024-02-16T04:29:44ZengElsevierICT Express2405-95952024-02-011012833SAR ship detection based on improved YOLOv5 and BiFPNChushi Yu0Yoan Shin1School of Electronic Engineering, Soongsil University, Seoul, South KoreaCorresponding author.; School of Electronic Engineering, Soongsil University, Seoul, South KoreaSynthetic aperture radar (SAR) is an advanced microwave sensor widely used in ocean monitoring, whose operation is not affected by light and weather. Ship targets in SAR images contain characteristically unclear contour information, a complex background, and display strong scattering. Ship detection algorithms based on convolutional neural networks achieved good results, albeit with many missed and false detections. To address this issue, we propose an improved scheme based on YOLOv5, that combines coordinate attention blocks and uses a bidirectional feature pyramid network for better feature fusion. Experimental results obtained with SAR images datasets demonstrate the effectiveness and applicability of the proposed model when applied for ship detection in SAR images. Compared to the original YOLOv5, the detection accuracy of the proposed method was increased from 81.28% to 88.27%, and the mean average precision was increased from 92.57% to 95.02%, which showed significant performance improvement by the proposed method in terms of detection accuracy and speed.http://www.sciencedirect.com/science/article/pii/S240595952300036XSynthetic aperture radarShip detectionYOLOv5Coordinate attention blockBidirectional feature pyramid network |
| spellingShingle | Chushi Yu Yoan Shin SAR ship detection based on improved YOLOv5 and BiFPN ICT Express Synthetic aperture radar Ship detection YOLOv5 Coordinate attention block Bidirectional feature pyramid network |
| title | SAR ship detection based on improved YOLOv5 and BiFPN |
| title_full | SAR ship detection based on improved YOLOv5 and BiFPN |
| title_fullStr | SAR ship detection based on improved YOLOv5 and BiFPN |
| title_full_unstemmed | SAR ship detection based on improved YOLOv5 and BiFPN |
| title_short | SAR ship detection based on improved YOLOv5 and BiFPN |
| title_sort | sar ship detection based on improved yolov5 and bifpn |
| topic | Synthetic aperture radar Ship detection YOLOv5 Coordinate attention block Bidirectional feature pyramid network |
| url | http://www.sciencedirect.com/science/article/pii/S240595952300036X |
| work_keys_str_mv | AT chushiyu sarshipdetectionbasedonimprovedyolov5andbifpn AT yoanshin sarshipdetectionbasedonimprovedyolov5andbifpn |