The excellent performance of graph convolutional networks (GCNs) on non-Euclidean data has drawn widespread attention from the hyperspectral image classification (HSIC) community, where the predefined ...

The goal of few-shot image classification is to learn a classifier that can be well generalized to the unseen classes with a few available labeled samples. One major challenge for few-shot learning is ...

CLIP (Contrastive Language-Image Pre-Training) is a neural network trained on a variety of (image, text) pairs. It can map images and text into the same latent space, so that they can be compared ...