Boundary-Aware Spatial and Frequency Dual-Domain Transformer for Remote Sensing Urban Images Segmentation
Author:
Affiliation:
1. College of Computer Science and Technology, China University of Petroleum (East China), Qingdao, China
2. School of Computer Science and Technology, Xi’an Jiaotong University, Xi’an, China
3. Yantai Iray Technology Company Ltd., Yantai, China
Funder
National Key Research and Development Program of China
National Natural Science Foundation of China
Natural Science Foundation of Shandong Province
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx8/36/10354519/10601227.pdf?arnumber=10601227
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1. An Active Deep Learning Approach for Minimally Supervised PolSAR Image Classification
2. Efficient Pyramidal GAN for Versatile Missing Data Reconstruction in Remote Sensing Images
3. Context-Based Multiscale Unified Network for Missing Data Reconstruction in Remote Sensing Images
4. Multiattention Network for Semantic Segmentation of Fine-Resolution Remote Sensing Images
5. A new fully convolutional neural network for semantic segmentation of polarimetric SAR imagery in complex land cover ecosystem
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