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Found 4 papers, 1 papers with code
A Deep Ensemble Learning Approach to Lung CT Segmentation for COVID-19 Severity Assessment
This is accomplished via a unique, end-to-end hierarchical network architecture and ensemble learning, which contribute to the segmentation and provide a measure for segmentation uncertainty.
The Role of Regularization in Shaping Weight and Node Pruning Dependency and Dynamics
The pressing need to reduce the capacity of deep neural networks has stimulated the development of network dilution methods and their analysis.
The Worrisome Impact of an Inter-rater Bias on Neural Network Training
In this paper, we highlight the issue of inter-rater bias as opposed to random inter-observer variability and demonstrate its influence on DNN training, leading to different segmentation results for the same input images.
DeepTract: A Probabilistic Deep Learning Framework for White Matter Fiber Tractography
We present DeepTract, a deep-learning framework for estimating white matter fibers orientation and streamline tractography.
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