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Found 4 papers, 3 papers with code
Contrastive Deep Encoding Enables Uncertainty-aware Machine-learning-assisted Histopathology
We show that our approach can reach the state-of-the-art (SOTA) for patch-level classification with only 1-10% randomly selected annotations compared to other SOTA approaches.
A Knowledge Distillation Framework For Enhancing Ear-EEG Based Sleep Staging With Scalp-EEG Data
Sleep plays a crucial role in the well-being of human lives.
Towards Interpretable Sleep Stage Classification Using Cross-Modal Transformers
Here, we propose a cross-modal transformer, which is a transformer-based method for sleep stage classification.
Ranked #2 on
Automatic Sleep Stage Classification
on Sleep-EDF
Automatic Sleep Stage Classification
General Classification
+3
Towards Accurate Cross-Domain In-Bed Human Pose Estimation
Majority of the contactless human pose estimation algorithms are based on RGB modality, causing ineffectiveness in in-bed pose estimation due to occlusions by blankets and varying illumination conditions.
