Brunel University Research Archive(BURA) preserves and enables easy and open access to all
types of digital content. It showcases Brunel's research outputs.
Research contained within BURA is open access, although some publications may be subject
to publisher imposed embargoes. All awarded PhD theses are also archived on BURA.
Browsing by Author Ardabili, SZ
Showing results 1 to 3 of 3
| Issue Date | Title | Author(s) |
|---|---|---|
| 29-Sep-2023 | Deep Learning for Detecting Multi-Level Driver Fatigue Using Physiological Signals: A Comprehensive Approach | Peivandi, M; Ardabili, SZ; Sheykhivand, S; Danishvar, S |
| 7-Jan-2024 | A Novel Approach for Automatic Detection of Driver Fatigue Using EEG Signals Based on Graph Convolutional Networks | Ardabili, SZ; Bahmani, S; Lahijan, LZ; Khaleghi, N; Sheykhivand, S; Danishvar, S |
| 23-Nov-2023 | Salient Arithmetic Data Extraction from Brain Activity via an Improved Deep Network | Khaleghi, N; Hashemi, S; Ardabili, SZ; Sheykhivand, S; Danishvar, S |