SGCT-Net: SAM-Guided Cross-Teaching Network for Weakly Supervised Semantic Segmentation for Generating High-Quality CAMs in High-Resolution Remote Sensing Imagery

Weakly supervised semantic segmentation (WSSS), particularly using image-level labels, has emerged as a pivotal solution to alleviate the burden of costly and labor-intensive pixel-level annotations typically required for remote sensing image interpretation. However, image-level label-based weakly s...

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Autori principali:	Yubo Jiang, Zheming Yuan, Tairan Zhou, Jing Chen, Fengying Xie, Zhiguo Jiang, Haopeng Zhang
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	IEEE 2026-01-01
Serie:	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Soggetti:	Boundary alignment class activation maps (CAMs) cross-teaching remote sensing (RS) segment anything model (SAM) weakly supervised semantic segmentation (WSSS)
Accesso online:	https://ieeexplore.ieee.org/document/11477155/
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