Compare learning: bi-attention network for few-shot learning

Li Ke, Meng Pan, Weigao Wen +1

Learning with few labeled data is a key challenge for visual recognition, as deep neural networks tend to overfit using a few samples only. One of the Few-shot learning methods cal…