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Deep Learning and Data Labeling for Medical Applications: First International Workshop, LABELS 2016, and Second International Workshop, DLMIA 2016, ... Athens, Greece, October 21, 2016, Proceedings - Softcover
Synopsis
Active learning.- Semi-supervised learning.- Reinforcement learning.- Domain adaptation and transfer learning.- Crowd-sourcing annotations and fusion of labels from different sources.- Data augmentation.- Modelling of label uncertainty.- Visualization and human-computer interaction.- Image description.- Medical imaging-based diagnosis.- Medical signal-based diagnosis.- Medical image reconstruction and model selection using deep learning techniques.- Meta-heuristic techniques for fine-tuning.- Parameter in deep learning-based architectures.- Applications based on deep learning techniques.
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