Liu et al., 2021 - Google Patents
DSAMNet: A deeply supervised attention metric based network for change detection of high-resolution imagesLiu et al., 2021
- Document ID
- 1364713469541850156
- Author
- Liu M
- Shi Q
- Publication year
- Publication venue
- 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS
External Links
Snippet
In view of the insufficient of current change detection, we propose a deeply-supervised attention metric-based network (DSAMNet) for bi-temporal image change detection. The DSAMNet contains a CBAM integrated change decision module to learn a change map …
- 238000001514 detection method 0 title abstract description 21
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- G06K9/4671—Extracting features based on salient regional features, e.g. Scale Invariant Feature Transform [SIFT] keypoints
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