In the field of unsupervised domain adaptation, most existing methods rely on global features that may not be able to capture fine-grained features, resulting in suboptimal transfer learning ...

The high cost of data annotation has become a major factor restricting the hyperspectral image (HSI) classification task. To address this issue, domain adaptation (DA) techniques have been developed ...

DCPRN: Distillation-Constrained Prototype Representation Network for Hyperspectral Image Incremental Classification. Abstract Oriented to adaptive recognition of the new land-cover categories, ...

Multi-crop Fusion Strategy Based on Prototype Assignment for Remote Sensing Image Scene Classification This code provides a PyTorch implementation and pretrained models for MFPC Abstract-The gap ...

In this paper, the Conceptual Space Theory, the Granular Computing approach and Machine Learning are bound in a novel common framework for solving some text categorization tasks with both standard ...