Few-shot learning continues to pose a challenge as it is inherently difficult for visual recognition models to generalize with limited labeled examples. When the training data is limited. the process of training and fine-tuning the model will be unstable and inefficient due to overfitting. In this paper. https://mainlandskateandsurfes.shop/product-category/womens-jackets/
NegCosIC: Negative Cosine Similarity-Invariance- Covariance Regularization for Few-Shot Learning
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