Self-Supervised Metric-Based Meta-Learning for Few-Shot Image classification
In this work, metric-based meta-learning models are proposed to learn a generic model embedding that can reduce the data shifting effect and thereby effectively distinguish the unseen samples. In addition, self-supervised learning is employed to mitigate the data scarcity problem by learning a robus...
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Format: | Thesis |
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2022
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