UGEL employs deep beta regression to estimate uncertainty in one forward pass, enabling faster convergence in edge learning for remote sensing image regression than active or semi-supervised baselines.
Pseudo-label: The simple and effi- cient semi-supervised learning method for deep neural net- works
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A semi-supervised 3D object detection framework with a learnable module for adaptive pseudo-label selection via score fusion, context-aware thresholds, and soft supervision.
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Uncertainty-Guided Edge Learning for Deep Image Regression in Remote Sensing
UGEL employs deep beta regression to estimate uncertainty in one forward pass, enabling faster convergence in edge learning for remote sensing image regression than active or semi-supervised baselines.
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Learning Adaptive Pseudo-Label Selection for Semi-Supervised 3D Object Detection
A semi-supervised 3D object detection framework with a learnable module for adaptive pseudo-label selection via score fusion, context-aware thresholds, and soft supervision.