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Computers in Biology and Medicine
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November 21, 2022
Druggable protein prediction using a multi-canal deep convolutional neural network based on autocovariance method
Mohammad Saber Iraji, Jafar Tanha, Mahboobeh Habibinejad
Journal of Biomedical Informatics
|
July 19, 2024
A novel deep learning model based on transformer and cross modality attention for classification of sleep stages
Sahar Hassanzadeh Mostafaei, Jafar Tanha, Amir Sharafkhaneh
Evolving Systems
|
April 16, 2024
AMTLDC: a new adversarial multi-source transfer learning framework to diagnosis of COVID-19
Hadi Alhares, Jafar Tanha, Mohammad Ali Balafar
Scientific Reports
|
November 27, 2025
Uncertainty-weighted semi-supervised learning with dynamic entropy masking and Bhattacharyya-regularized loss
Mohammed Talal Ghazal, Jafar Tanha, Nasrin Shahi, et al.
Computers in Biology and Medicine
|
April 10, 2026
A novel consistency-guided and pseudo labeled training for weakly-semi-supervised medical image segmentation
Mahdi Zarrin, Jafar Tanha, Amin Kazempour, et al.
IEEE Transactions on Neural Networks and Learning Systems
|
December 6, 2023
AEVAE: Adaptive Evolutionary Autoencoder for Anomaly Detection in Time Series
Ali Jameel Hashim, M A Balafar, Jafar Tanha, et al.
Plos One
|
January 2, 2026
DSN-STC: Leveraging Siamese networks for optimized short text clustering
Mahdi Molaei, Mohammad-Reza Feizi-Derakhshi, Mohammad-Ali Balafar, et al.
Data in Brief
|
September 29, 2025
Planes of thought dataset: A new dataset for the measurement of human thought by artificial intelligence model based on Cloninger's theory
Atra Joudaki, Leyli Mohammad Khanli, Alireza Farnam, et al.
Computers in Biology and Medicine
|
March 19, 2024
A deep ensemble medical image segmentation with novel sampling method and loss function
SeyedEhsan Roshan, Jafar Tanha, Mahdi Zarrin, et al.
IEEE Transactions on Neural Networks and Learning Systems
|
October 31, 2025
Multiscale Contrastive Learning for Node Clustering Based on Variational Graph Auto-Encoder
Nazila Pourhaji Aghayengejeh, M A Balafar, Jafar Tanha, et al.
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Showing results (1-10 of 11) with videos related to
Sort By:
Page
of 2
Computers in Biology and Medicine
|
November 21, 2022
Druggable protein prediction using a multi-canal deep convolutional neural network based on autocovariance method
Mohammad Saber Iraji, Jafar Tanha, Mahboobeh Habibinejad
Journal of Biomedical Informatics
|
July 19, 2024
A novel deep learning model based on transformer and cross modality attention for classification of sleep stages
Sahar Hassanzadeh Mostafaei, Jafar Tanha, Amir Sharafkhaneh
Evolving Systems
|
April 16, 2024
AMTLDC: a new adversarial multi-source transfer learning framework to diagnosis of COVID-19
Hadi Alhares, Jafar Tanha, Mohammad Ali Balafar
Scientific Reports
|
November 27, 2025
Uncertainty-weighted semi-supervised learning with dynamic entropy masking and Bhattacharyya-regularized loss
Mohammed Talal Ghazal, Jafar Tanha, Nasrin Shahi, et al.
Computers in Biology and Medicine
|
April 10, 2026
A novel consistency-guided and pseudo labeled training for weakly-semi-supervised medical image segmentation
Mahdi Zarrin, Jafar Tanha, Amin Kazempour, et al.
IEEE Transactions on Neural Networks and Learning Systems
|
December 6, 2023
AEVAE: Adaptive Evolutionary Autoencoder for Anomaly Detection in Time Series
Ali Jameel Hashim, M A Balafar, Jafar Tanha, et al.
Plos One
|
January 2, 2026
DSN-STC: Leveraging Siamese networks for optimized short text clustering
Mahdi Molaei, Mohammad-Reza Feizi-Derakhshi, Mohammad-Ali Balafar, et al.
Data in Brief
|
September 29, 2025
Planes of thought dataset: A new dataset for the measurement of human thought by artificial intelligence model based on Cloninger's theory
Atra Joudaki, Leyli Mohammad Khanli, Alireza Farnam, et al.
Computers in Biology and Medicine
|
March 19, 2024
A deep ensemble medical image segmentation with novel sampling method and loss function
SeyedEhsan Roshan, Jafar Tanha, Mahdi Zarrin, et al.
IEEE Transactions on Neural Networks and Learning Systems
|
October 31, 2025
Multiscale Contrastive Learning for Node Clustering Based on Variational Graph Auto-Encoder
Nazila Pourhaji Aghayengejeh, M A Balafar, Jafar Tanha, et al.
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of 2