Category-sensitive semi-supervised semantic segmentation framework for land-use/land-cover mapping with optical remote sensing images

Author:

Chen JifaORCID,Chen Gang,Zhang Li,Huang Min,Luo Jin,Ding Mingjun,Ge Yong

Publisher

Elsevier BV

Reference52 articles.

1. Semantic labeling of high-resolution images using EfficientUNets and transformers;Almarzouqi;IEEE Trans. Geosci. Remote. Sens.,2023

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3. Segnet: A deep convolutional encoder-decoder architecture for image segmentation;Badrinarayanan;IEEE Trans. Pattern Anal. Mach. Intell.,2017

4. Superpixel-based multiscale CNN approach toward multiclass object segmentation from UAV-captured aerial images;Behera;IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens.,2023

5. Semi-Supervised Semantic Segmentation in Earth Observation: The MiniFrance suite, dataset analysis and multi-task network study;Castillo-Navarro;Mach. Learn.,2021

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