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ImageNet augmentation
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Classroom Contents
Unsupervised Meta-Learning for Few-Shot Image Classification
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- 1 Intro
- 2 Outline
- 3 Problem definition
- 4 What is a task?
- 5 What we learn during meta-learning?
- 6 Model-agnostic meta-learning
- 7 Action recognition
- 8 Unsupervised Meta-learning with Tasks constructe by Random sampling and Augmentation UMTRA
- 9 Omniglot augmentation
- 10 Auto augmentation
- 11 ImageNet augmentation
- 12 Few-shot learning benchmarks
- 13 Ablation studies Omniglot
- 14 Ablation studies Mini-Imagenet
- 15 CelebA task generation
- 16 Video augmentation (self supervision)
- 17 Features visualization by t-SNE
- 18 t-SNE visualization of the last hidden layer
