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Cognitive Neurodynamics
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November 18, 2024
EEG-based schizophrenia detection using fusion of effective connectivity maps and convolutional neural networks with transfer learning
Sara Bagherzadeh, Ahmad Shalbaf
Physical and Engineering Sciences in Medicine
|
September 14, 2020
Transfer learning with deep convolutional neural network for automated detection of schizophrenia from EEG signals
Ahmad Shalbaf, Sara Bagherzadeh, Arash Maghsoudi
Computers in Biology and Medicine
|
May 3, 2022
Detection of schizophrenia using hybrid of deep learning and brain effective connectivity image from electroencephalogram signal
Sara Bagherzadeh, Mohsen Sadat Shahabi, Ahmad Shalbaf
Cognitive Neurodynamics
|
October 14, 2022
Emotion recognition using effective connectivity and pre-trained convolutional neural networks in EEG signals
Sara Bagherzadeh, Keivan Maghooli, Ahmad Shalbaf, et al.
Scientific Reports
|
April 21, 2024
Classification of mental workload using brain connectivity and machine learning on electroencephalogram data
MohammadReza Safari, Reza Shalbaf, Sara Bagherzadeh, et al.
Computer Methods in Biomechanics and Biomedical Engineering
|
August 1, 2024
Classification of mental workload with EEG analysis by using effective connectivity and a hybrid model of CNN and LSTM
MohammadReza Safari, Reza Shalbaf, Sara Bagherzadeh, et al.
Basic and Clinical Neuroscience
|
June 22, 2023
A Hybrid EEG-based Emotion Recognition Approach Using Wavelet Convolutional Neural Networks and Support Vector Machine
Sara Bagherzadeh, Keivan Maghooli, Ahmad Shalbaf, et al.
Computers in Biology and Medicine
|
September 14, 2023
Emotion recognition in EEG signals using deep learning methods: A review
Mahboobeh Jafari, Afshin Shoeibi, Marjane Khodatars, et al.
Brain Sciences
|
March 27, 2026
Towards the Development of a Deep Learning Framework Using Adaptive and Non-Adaptive Time-Frequency Features for EEG-Based Depression Therapy Prediction
Hesam Akbari, Sara Bagherzadeh, Javid Farhadi Sedehi, et al.
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of 1
Search research articles
Search
Showing results (1-10 of 9) with videos related to
Sort By:
Page
of 1
Cognitive Neurodynamics
|
November 18, 2024
EEG-based schizophrenia detection using fusion of effective connectivity maps and convolutional neural networks with transfer learning
Sara Bagherzadeh, Ahmad Shalbaf
Physical and Engineering Sciences in Medicine
|
September 14, 2020
Transfer learning with deep convolutional neural network for automated detection of schizophrenia from EEG signals
Ahmad Shalbaf, Sara Bagherzadeh, Arash Maghsoudi
Computers in Biology and Medicine
|
May 3, 2022
Detection of schizophrenia using hybrid of deep learning and brain effective connectivity image from electroencephalogram signal
Sara Bagherzadeh, Mohsen Sadat Shahabi, Ahmad Shalbaf
Cognitive Neurodynamics
|
October 14, 2022
Emotion recognition using effective connectivity and pre-trained convolutional neural networks in EEG signals
Sara Bagherzadeh, Keivan Maghooli, Ahmad Shalbaf, et al.
Scientific Reports
|
April 21, 2024
Classification of mental workload using brain connectivity and machine learning on electroencephalogram data
MohammadReza Safari, Reza Shalbaf, Sara Bagherzadeh, et al.
Computer Methods in Biomechanics and Biomedical Engineering
|
August 1, 2024
Classification of mental workload with EEG analysis by using effective connectivity and a hybrid model of CNN and LSTM
MohammadReza Safari, Reza Shalbaf, Sara Bagherzadeh, et al.
Basic and Clinical Neuroscience
|
June 22, 2023
A Hybrid EEG-based Emotion Recognition Approach Using Wavelet Convolutional Neural Networks and Support Vector Machine
Sara Bagherzadeh, Keivan Maghooli, Ahmad Shalbaf, et al.
Computers in Biology and Medicine
|
September 14, 2023
Emotion recognition in EEG signals using deep learning methods: A review
Mahboobeh Jafari, Afshin Shoeibi, Marjane Khodatars, et al.
Brain Sciences
|
March 27, 2026
Towards the Development of a Deep Learning Framework Using Adaptive and Non-Adaptive Time-Frequency Features for EEG-Based Depression Therapy Prediction
Hesam Akbari, Sara Bagherzadeh, Javid Farhadi Sedehi, et al.
Page
of 1