IEEE

WavTSK: An Interpretable Fuzzy Network With Learnable Wavelet-Based Feature Extraction for Motor Imagery EEG Decoding

Abstract: Decoding motor imagery (MI) from electroencephalogram (EEG) signals is a cornerstone of brain–computer interface (BCI) systems. However, existing methods often face a critical tradeoff ...
IEEE

Bi-ACTCNet: A Bidirectional Channel Attention and Mutual-Cross-Attention Temporal Feature Extraction Network for Motor-Rest Classification in Motor Imagery

Abstract: Combining brain–computer interface (BCI) technology with the Internet of Things (IoT) for practical motor rehabilitation applications is a critical research direction aimed at enhancing the ...
IEEE

Graph-Based Radiomics Feature Extraction From 2D Retina Images

Abstract: Medical image analysis offers valuable visual support for clinical decision-making, yet the incorporation of quantitative data is essential for deeper diagnostic insight. The radiomics ...
IEEE

A Hybrid Feature Extraction and Classification Framework for Depression Detection using Deep Learning and Machine Learning Techniques

Abstract: Depression is most common mental disorder that is affecting approximately 280 million individuals in the world. The stigma and lack of acceptance and awareness is still influencing people ...