Research Assistant Muhammet Mustafa Yurdakul from Istanbul Gelisim University has contributed to an important academic study published in the internationally recognized journal Signal, Image and Video Processing. The article, co-authored with Indrit Myderrizi and Ali H. Abdulwahhab, is entitled: “PAFWF-EEGC Net: Parallel Adaptive Feature Weight Fusion Based on EEG-Dynamic Characteristics Using Channels Neural Network for Driver Drowsiness Detection.”
Published in 2025, the study introduces an innovative artificial intelligence-based model aimed at detecting driver drowsiness through EEG (electroencephalogram) signals. By employing parallel adaptive feature weight fusion and channel-based neural networks, the proposed method seeks to provide faster and more accurate assessments of drivers’ attention levels.
This research makes a significant contribution to the fields of driver safety and AI-powered healthcare applications. Furthermore, the publication has been indexed in leading international databases, including SCI-Expanded, Scopus, Compendex, INSPEC, and zbMATH.
Click here to access the academic study.
Istanbul Gelisim University continues to advance its scientific productivity through the international contributions of its academic staff.
