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Dataset-dependence of supervised learning methods
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Classroom Contents
Self-supervised Deep Learning for Image Recovery - SIAM-IS Virtual Seminar
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- 1 Intro
- 2 Inverse problem: Image deblurring
- 3 Image recovery/reconstruction
- 4 Regularization methods for image recovery
- 5 Non-local self-similarity prior of images
- 6 Deep learning for linear inverse problem
- 7 An example: Unrolling half-quadratic splitting scheme
- 8 Dataset-dependence of supervised learning methods
- 9 A self-supervised approach to general image recovery proble
- 10 Part 1: Data augmentation & Self-supervised loss function
- 11 Data augmentation via Bernoulli random sampling
- 12 Recap: Self-supervised loss function
- 13 Testing with Bayesian neural network
- 14 Experiments on removing Gaussian white noise from images
- 15 Stability of training
- 16 Visual inspection
