MATNet: multiattention Transformer network for cropland semantic segmentation in remote sensing images-Reference-Cited by-同舟云学术

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MATNet: multiattention Transformer network for cropland semantic segmentation in remote sensing images

Published:2024-08-19 Issue:1 Volume:17 Page:
ISSN:1753-8947
Container-title:International Journal of Digital Earth
language:en
Short-container-title:International Journal of Digital Earth

Author:

Zhang Zixuan¹^ORCID,Huang Liang¹²^ORCID,Tang Bo-Hui¹²^ORCID,Le Weipeng¹^ORCID,Wang Meiqi¹^ORCID,Cheng Jiapei¹^ORCID,Wu Qiang¹^ORCID

Affiliation:

1. Faculty of Land Resources Engineering, Kunming University of Science and Technology, Kunming, People’ s Republic of People’s Republic of China

2. Key Laboratory of Plateau Remote Sensing, Yunnan Provincial Department of Education, Kunming University of Science and Technology, Kunming, People’s Republic of China

Funder

National Natural Science Foundation of China

Yunnan Fundamental Research Project

The Science and Technology Program of Geological Institution of Hunan Province

Yunnan Province Key Research and Development Program

Hunan Provincial Natural Science Foundation of China

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/17538947.2024.2392845

Reference36 articles.

1. Case instance segmentation of small farmland based on Mask R-CNN of feature pyramid network with double attention mechanism in high resolution satellite images

2. TransAttUnet: Multi-Level Attention-Guided U-Net With Transformer for Medical Image Segmentation

3. Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation

4. Distilling Segmenters From CNNs and Transformers for Remote Sensing Images’ Semantic Segmentation

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