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Found 3 papers, 1 papers with code
Uncertainty-driven and Adversarial Calibration Learning for Epicardial Adipose Tissue Segmentation
we propose a novel feature latent space multilevel supervision network (SPDNet) with uncertainty-driven and adversarial calibration learning to enhance segmentation for more accurate EAT volume estimation.
MGCT: Mutual-Guided Cross-Modality Transformer for Survival Outcome Prediction using Integrative Histopathology-Genomic Features
The rapidly emerging field of deep learning-based computational pathology has shown promising results in utilizing whole slide images (WSIs) to objectively prognosticate cancer patients.
A TSK-type Convolutional Recurrent Fuzzy Network for Predicting Driving Fatigue
To effectively predict driving fatigue, this paper proposes a new deep learning framework called TSK-type Convolution Recurrent Fuzzy Network (TCRFN) based on the spatial and temporal characteristics of EEG signals.
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