SMNet: Symmetric Multi-Task Network for Semantic Change Detection in Remote Sensing Images Based on CNN and Transformer Article Swipe
Yiting Niu
,
Haitao Guo
,
Jun Lu
,
Lei Ding
,
Donghang Yu
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/rs15040949
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/rs15040949
Deep learning has achieved great success in remote sensing image change detection (CD). However, most methods focus only on the changed regions of images and cannot accurately identify their detailed semantic categories. In addition, most CD methods using convolutional neural networks (CNN) have difficulty capturing sufficient global information from images. To address the above issues, we propose a novel symmetric multi-task network (SMNet) that integrates global and local information for semantic change detection (SCD) in this paper. Specifically, we employ a hybrid unit consisting of pre-activated residual blocks (PR) and transformation blocks (TB) to construct the (PRTB) backbone, which obtains more abundant semantic features with local and global information from bi-temporal images. To accurately capture fine-grained changes, the multi-content fusion module (MCFM) is introduced, which effectively enhances change features by distinguishing foreground and background information in complex scenes. In the meantime, the multi-task prediction branches are adopted, and the multi-task loss function is used to jointly supervise model training to improve the performance of the network. Extensive experimental results on the challenging SECOND and Landsat-SCD datasets, demonstrate that our SMNet obtains 71.95% and 85.65% at mean Intersection over Union (mIoU), respectively. In addition, the proposed SMNet achieves 20.29% and 51.14% at Separated Kappa coefficient (Sek) on the SECOND and Landsat-SCD datasets, respectively. All of the above proves the effectiveness and superiority of the proposed method.
Related Topics
Concepts
Computer science
Residual
Artificial intelligence
Convolutional neural network
Change detection
Pattern recognition (psychology)
Task (project management)
Intersection (aeronautics)
Transformation (genetics)
Deep learning
Algorithm
Engineering
Biochemistry
Management
Chemistry
Economics
Gene
Aerospace engineering
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/rs15040949
- https://www.mdpi.com/2072-4292/15/4/949/pdf?version=1675934239
- OA Status
- gold
- Cited By
- 55
- References
- 51
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4319966415
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4319966415Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/rs15040949Digital Object Identifier
- Title
-
SMNet: Symmetric Multi-Task Network for Semantic Change Detection in Remote Sensing Images Based on CNN and TransformerWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-02-09Full publication date if available
- Authors
-
Yiting Niu, Haitao Guo, Jun Lu, Lei Ding, Donghang YuList of authors in order
- Landing page
-
https://doi.org/10.3390/rs15040949Publisher landing page
- PDF URL
-
https://www.mdpi.com/2072-4292/15/4/949/pdf?version=1675934239Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://www.mdpi.com/2072-4292/15/4/949/pdf?version=1675934239Direct OA link when available
- Concepts
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Computer science, Residual, Artificial intelligence, Convolutional neural network, Change detection, Pattern recognition (psychology), Task (project management), Intersection (aeronautics), Transformation (genetics), Deep learning, Algorithm, Engineering, Biochemistry, Management, Chemistry, Economics, Gene, Aerospace engineeringTop concepts (fields/topics) attached by OpenAlex
- Cited by
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55Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 24, 2024: 26, 2023: 5Per-year citation counts (last 5 years)
- References (count)
-
51Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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