A soft K-means prototype classifier with adaptive receptive fields is claimed to keep near-perfect few-shot accuracy under 60% label noise, but the paper omits code, hyperparameters, and pretraining disclosure.
An image is worth 16x16 words: Transformers for image recognition at scale, in: Proceedings of the International Conference on Learning Representations (ICLR)
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RoNFA: Robust Neural Field-based Approach for Few-Shot Image Classification with Noisy Labels
A soft K-means prototype classifier with adaptive receptive fields is claimed to keep near-perfect few-shot accuracy under 60% label noise, but the paper omits code, hyperparameters, and pretraining disclosure.