Sampling Equivariant Self-Attention Networks for Object Detection in Aerial Images
Objects in aerial images show greater variations in scale and orientation than in other images, making them harder to detect using vanilla deep convolutional neural networks. Networks with sampling equivariance can adapt sampling from input feature maps to object transformation, allowing a convoluti...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 32(2023) vom: 16., Seite 6413-6425
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| 1. Verfasser: |
Yang, Guo-Ye
(VerfasserIn) |
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| Weitere Verfasser: |
Li, Xiang-Li,
Xiao, Zi-Kai,
Mu, Tai-Jiang,
Martin, Ralph R,
Hu, Shi-Min |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2023
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
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| Schlagworte: | Journal Article |
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