More recently, vision transformer (ViT) has shown competitive performance with
convolutional neural network (CNN) on computer vision tasks, which provided more …

With the development of few-shot learning, significant progress has been achieved in
hyperspectral image classification using related networks, leading to improved classification …

Nowadays, foundation models have demonstrated exceptional performance across
numerous downstream tasks. However, the effective application of these models to …

卷积神经网络被广泛应用于图像识别领域并且展现出**大的特征提取能力,
但它只能处理欧氏空间的结构化数据, 无法适用于非结构化数据的处理. 为应对该限制 …

Graph neural networks (GNNs) offer a potent framework for learning and representing data
with graph structures. In the context of hyperspectral images (HSIs) classification tasks …

Due to the complexity of hyperspectral data and the scarcity of labeled samples,
unsupervised clustering segmentation has become a hot spot of interest in remote sensing …

Nowadays, various types of foundational models have emerged, showcasing remarkable
performance across a multitude of downstream tasks. However, in the domain of …