Semantic segmentation of high-resolution remote sensing images based on a class feature attention mechanism fused with Deeplabv3+-Reference-Cited by-同舟云学术

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Semantic segmentation of high-resolution remote sensing images based on a class feature attention mechanism fused with Deeplabv3+

Published:2022-01 Issue: Volume:158 Page:104969
ISSN:0098-3004
Container-title:Computers & Geosciences
language:en
Short-container-title:Computers & Geosciences

Author:

Wang Zhimin,Wang Jiasheng,Yang Kun,Wang Limeng,Su Fanjie,Chen Xinya

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Computers in Earth Sciences,Information Systems

Reference52 articles.

1. SegNet: a deep convolutional encoder-decoder architecture for image segmentation;Badrinarayanan;IEEE Trans. Pattern Anal. Mach. Intell.,2017

2. FCM: the fuzzy c-means clustering algorithm;Bezdek;Comput. Geosci.,1984

3. A top-down approach for semantic segmentation of big remote sensing images;Boulila;Earth Sci. India,2019

4. Multi-scale segmentation of remote sensing image based on watershed transformation;Cai;2009 Joint Urban Remote Sensing Event,2009

5. MFANet: a multi-level feature aggregation network for semantic segmentation of land cover;Chen;Rem. Sens.,2021

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