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Found 3 papers, 1 papers with code
A Universal Knowledge Embedded Contrastive Learning Framework for Hyperspectral Image Classification
Therefore, we propose a universal knowledge embedded contrastive learning framework (KnowCL) for supervised, unsupervised, and semisupervised HSI classification, which largely closes the gap between HSI classification models between pocket models and standard vision backbones.
Adapting Vision Transformer for Efficient Change Detection
Most change detection models based on vision transformers currently follow a "pretraining then fine-tuning" strategy.
Unpaired MRI Super Resolution with Contrastive Learning
To this end, we propose an unpaired MRI SR approach that employs contrastive learning to enhance SR performance with limited HR training data.
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