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Evaluation of Semi-supervised Semantic Segmentation for Remote Sensing, Medical Imaging, and Machine Vision Settings

Semi-supervised semantic segmentation (S<sup>4</sup>) has garnered significant attention in recent years due to the time-consuming and costly process of creating pixel-level annotations. Instead of only relying on labeled data, semi-supervised approaches leverage both labeled and unlabeled data to m...

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Bibliografische gegevens
Hoofdauteurs: S. Landgraf, J. Huber, M. Hillemann, M. Ulrich
Formaat: Artigo
Taal:Inglês
Gepubliceerd in: Copernicus Publications 2025-07-01
Reeks:ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online toegang:https://isprs-annals.copernicus.org/articles/X-G-2025/527/2025/isprs-annals-X-G-2025-527-2025.pdf
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