Uncertainty-driven training for three-dimensional calibrated lung nodule classification
eess.IV, cs.CV
Submitted: 2026-09-17
Updated: 2026-09-17
Terminology
Sources
- Revisiting Essential and Nonessential Settings of Evidential Deep Learning
- An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
- Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
- A Survey of Uncertainty in Deep Neural Networks
- On Calibration of Modern Neural Networks
- Deep Residual Learning for Image Recognition
- A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks
- Densely Connected Convolutional Networks
- Adam: A Method for Stochastic Optimization
- Focal Loss for Dense Object Detection
- Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
- PyTorch: An Imperative Style, High-Performance Deep Learning Library
- Evidential Deep Learning to Quantify Classification Uncertainty
- EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
- Uncertainty-aware Self-ensembling Model for Semi-supervised 3D Left Atrium Segmentation
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