Data from multimodalities bring complementary information for deep learning-based medical image classification models. However, data fusion methods simply concatenating features or images barely ...

Abstract: Deep learning-based hyperspectral image (HSI) classification methods have recently shown excellent performance. However, the success of these deep learning methods mainly relies on the deep ...

The coral-reef-training AWS S3 bucket provides a single, open, well-structured, growing, community-sourced repository of coral reef image classification training data. Hosted at ...

Hyperspectral images are rich in spectral and spatial information, providing a detailed and comprehensive description of objects, which makes hyperspectral image analysis technology essential in ...

Humans are innately curious and we're surrounded by people and things that pique our interest. Maybe a cute pair of shoes catches your eye while scrolling through your social media newsfeeds. Or it ...

The model can be trained on a single GPU with more than 12 GB of memory.

In response to the problem of inadequate utilization of local information in PolSAR image classification using Vision Transformer in existing studies, this paper proposes a Vision Transformer method ...

PR1, W1, T51, F58, SL4, KL3, SM11. This is not a test to crack a code. But you will see a series of letter and number combinations while engaging with the Paralympics in Paris. At the Olympics, there ...

The automated classification of rock images is of paramount importance in geological analysis, as it serves as the foundational criterion for the categorization of rock lithology. Despite recent ...