IEEE

A Novel Transformer-KAN Network Utilizes Multimodality Contrastive Learning and Mask Reconstruction for Remote Sensing Classification

Abstract: Contrastive learning is a promising paradigm in the multimodal few-shot domain, leveraging images captured from different sensors as diverse perspectives of the same ground objects. However, ...
Scientific Research Publishing

Cross-Population Transfer Learning for Antidepressant Treatment Response Prediction: A SHAP-Based Explainability Approach Using Synthetic Multi-Ethnic Data ()

de Filippis, R. and Al Foysal, A. (2026) Cross-Population Transfer Learning for Antidepressant Treatment Response Prediction: A SHAP-Based Explainability Approach Using Synthetic Multi-Ethnic Data.
IEEE

Remote Sensing Scene Image Classification with Swin Transformer-Based Transfer Learning

Abstract: In remote sensing classification problems, high visual similarity between scenes reduces the classification performance of traditional methods. Therefore, advanced deep neural network models ...
EurekAlert!

AI-accelerated gas sensing: a first-principles–guided machine learning platform for black phosphorus sensors

Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...