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Semantic image segmentation: Two decades of research
Semantic image segmentation (SiS) plays a fundamental role in a broad variety of computer
vision applications, providing key information for the global understanding of an image. This …
vision applications, providing key information for the global understanding of an image. This …
Advances and challenges in deep learning-based change detection for remote sensing images: A review through various learning paradigms
Change detection (CD) in remote sensing (RS) imagery is a pivotal method for detecting
changes in the Earth's surface, finding wide applications in urban planning, disaster …
changes in the Earth's surface, finding wide applications in urban planning, disaster …
Querying labeled for unlabeled: Cross-image semantic consistency guided semi-supervised semantic segmentation
Semi-supervised semantic segmentation aims to learn a semantic segmentation model via
limited labeled images and adequate unlabeled images. The key to this task is generating …
limited labeled images and adequate unlabeled images. The key to this task is generating …
Distilling self-supervised vision transformers for weakly-supervised few-shot classification & segmentation
We address the task of weakly-supervised few-shot image classification and segmentation,
by leveraging a Vision Transformer (ViT) pretrained with self-supervision. Our proposed …
by leveraging a Vision Transformer (ViT) pretrained with self-supervision. Our proposed …
Pseudo-label guided image synthesis for semi-supervised covid-19 pneumonia infection segmentation
Coronavirus disease 2019 (COVID-19) has become a severe global pandemic. Accurate
pneumonia infection segmentation is important for assisting doctors in diagnosing COVID …
pneumonia infection segmentation is important for assisting doctors in diagnosing COVID …
A survey on semi-supervised semantic segmentation
A Peláez-Vegas, P Mesejo, J Luengo - ar** with satellite SAR and optical data
S Ge, H Gu, W Su, J Praks… - IEEE Journal of Selected …, 2022 - ieeexplore.ieee.org
In this study, we introduce an improved semisupervised deep learning approach, and
demonstrate its suitability for modeling the relationship between forest structural parameters …
demonstrate its suitability for modeling the relationship between forest structural parameters …
Fuzzy positive learning for semi-supervised semantic segmentation
Semi-supervised learning (SSL) essentially pursues class boundary exploration with less
dependence on human annotations. Although typical attempts focus on ameliorating the …
dependence on human annotations. Although typical attempts focus on ameliorating the …