SSNet: A Novel Transformer and CNN Hybrid Network for Remote Sensing Semantic Segmentation
Author:
Affiliation:
1. College of Information Engineering, Shanghai Maritime University, Shanghai, China
2. Baidu, Beijing, China
3. College of Resources and Environmental Engineering, Tianshui Normal University, Tianshui, China
Funder
National Natural Science Foundation of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/4609443/10330207/10380705.pdf?arnumber=10380705
Reference56 articles.
1. SegNeXt: Rethinking convolutional attention design for semantic segmentation;Guo,2022
2. Transformer and CNN Hybrid Deep Neural Network for Semantic Segmentation of Very-High-Resolution Remote Sensing Imagery
3. Semantic Segmentation of Remote Sensing Images With Sparse Annotations
4. A 2.5D semantic segmentation of the pancreas using attention guided dual context embedded U-Net
5. A Two-Phase Approach using Mask R-CNN and 3D U-Net for High-Accuracy Automatic Segmentation of Pancreas in CT Imaging
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