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Sevda Zafarmandi
Sevda Zafarmandi
Southern Methodist University
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Deep Learning for Detecting Multi-Level Driver Fatigue Using Physiological Signals: A Comprehensive Approach
M Peivandi, SZ Ardabili, S Sheykhivand, S Danishvar
Sensors 23 (19), 8171, 2023
112023
Salient Arithmetic Data Extraction from Brain Activity via an Improved Deep Network
N Khaleghi, S Hashemi, SZ Ardabili, S Sheykhivand, S Danishvar
Sensors 23 (23), 9351, 2023
82023
A Novel Approach for Automatic Detection of Driver Fatigue Using EEG Signals Based on Graph Convolutional Networks
SZ Ardabili, S Bahmani, LZ Lahijan, N Khaleghi, S Sheykhivand, ...
Sensors 24 (2), 364, 2024
72024
EEG-based functional connectivity analysis of brain abnormalities: A review study
N Khaleghi, S Hashemi, M Peivandi, SZ Ardabili, M Behjati, ...
Informatics in Medicine Unlocked, 101476, 2024
12024
A New Method to Improve Noise Cancellation in Medical Images Using Filtration and Artificial Neural Networks
سوداظفرمندی اردبیلی، رامین سلیمانی، سبلان دانشور
Fifth International Conference on Technology Development in Iranian …, 2021
2021
Fusion medical images using feature extraction based on wavelet transform
سوداظفرمندی اردبیلی، سبلان دانشور
14th International Conference on Information technology, computer and …, 2020
2020
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