A Crossmodal Multiscale Fusion Network for Semantic Segmentation of Remote Sensing Data-Reference-Cited by-同舟云学术

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A Crossmodal Multiscale Fusion Network for Semantic Segmentation of Remote Sensing Data

Published:2022 Issue: Volume:15 Page:3463-3474
ISSN:1939-1404
Container-title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
language:
Short-container-title:IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Author:

Ma Xianping¹^ORCID,Zhang Xiaokang¹^ORCID,Pun Man-On¹^ORCID

Affiliation:

1. School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, China

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Shenzhen Science and Technology Innovation Committee

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Atmospheric Science,Computers in Earth Sciences

Link

http://xplorestaging.ieee.org/ielx7/4609443/9656571/09749821.pdf?arnumber=9749821

Reference46 articles.

1. SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

2. Very deep convolutional networks for large-scale image recognition;simonyan;Proc 3rd Int Conf Learn Representations,0

3. Swin Transformer: Hierarchical Vision Transformer using Shifted Windows

4. A Novel Transformer Based Semantic Segmentation Scheme for Fine-Resolution Remote Sensing Images

5. TransBTS: Multimodal Brain Tumor Segmentation Using Transformer

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