Histopathological image classification stands as a cornerstone in the pathological diagnosis workflow, yet it remains challenging due to the inherent complexity of histopathological images. Recently, ...

Domain adaptation (DA)-based cross-domain hyperspectral image (HSI) classification methods have garnered significant attention. The majority of DA techniques utilize models based on convolutional ...

To obtain light ensemble model through clearly explained effective ensemble member selection and finding data representation in various valuable forms are major challenges in medical image ...

Convolutional neural networks (CNNs) have made breakthrough in remote sensing image processing due to their ability to extract deep features. This letter proposes a remote sensing image scene ...

Hyperspectral image (HSI) classification has been extensively studied in the context of Earth observation. However, its application in Mars exploration remains limited. Although convolutional neural ...

The work in this project helps in improving the classification of skin diseases using the combination of Generative Adversarial Networks (GANs) and Convolutional Neural Networks (CNNs). GANs were used ...

High-resolution remote sensing image (HRSI) scene classification often faces challenges; for example, the intraclass similarity is low, but the interclass similarity is high due to complex backgrounds ...