Small-Scale Ship Detection for SAR Remote Sensing Images Based on Coordinate-Aware Mixed Attention and Spatial Semantic Joint Context Article Swipe
Zhengjie Jiang
,
Yupei Wang
,
Xiaoqi Zhou
,
Liang Chen
,
Chang Yuan
,
Dongsheng Song
,
Hao Shi
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/smartcities6030076
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/smartcities6030076
With the rapid development of deep learning technology in recent years, convolutional neural networks have gained remarkable progress in SAR ship detection tasks. However, noise interference of the background and inadequate appearance features of small-scale objects still pose challenges. To tackle these issues, we propose a small ship detection algorithm for SAR images by means of a coordinate-aware mixed attention mechanism and spatial semantic joint context method. First, the coordinate-aware mixed attention mechanism innovatively combines coordinate-aware channel attention and spatial attention to achieve coordinate alignment of mixed attention features. In this way, attention with finer spatial granularity is conducive to strengthening the focusing ability on small-scale objects, thereby suppressing the background clutters accurately. In addition, the spatial semantic joint context method exploits the local and global environmental information jointly. The detailed spatial cues contained in the multi-scale local context and the generalized semantic information encoded in the global context are used to enhance the feature expression and distinctiveness of small-scale ship objects. Extensive experiments are conducted on the LS-SSDD-v1.0 and the HRSID dataset. The results with an average precision of 77.23% and 90.85% on the two datasets show the effectiveness of the proposed methods.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/smartcities6030076
- https://www.mdpi.com/2624-6511/6/3/76/pdf?version=1686795555
- OA Status
- gold
- Cited By
- 5
- References
- 37
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4380996142
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- OpenAlex ID
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https://openalex.org/W4380996142Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/smartcities6030076Digital Object Identifier
- Title
-
Small-Scale Ship Detection for SAR Remote Sensing Images Based on Coordinate-Aware Mixed Attention and Spatial Semantic Joint ContextWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-06-15Full publication date if available
- Authors
-
Zhengjie Jiang, Yupei Wang, Xiaoqi Zhou, Liang Chen, Chang Yuan, Dongsheng Song, Hao ShiList of authors in order
- Landing page
-
https://doi.org/10.3390/smartcities6030076Publisher landing page
- PDF URL
-
https://www.mdpi.com/2624-6511/6/3/76/pdf?version=1686795555Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/2624-6511/6/3/76/pdf?version=1686795555Direct OA link when available
- Concepts
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Computer science, Context (archaeology), Spatial contextual awareness, Scale (ratio), Spatial analysis, Artificial intelligence, Feature (linguistics), Pattern recognition (psychology), Computer vision, Remote sensing, Cartography, Geography, Philosophy, Archaeology, LinguisticsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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5Total citation count in OpenAlex
- Citations by year (recent)
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2025: 2, 2024: 1, 2023: 2Per-year citation counts (last 5 years)
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37Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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