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Shervin Minaee

Showing results (1-10 of 10) with videos related to

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IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society|February 1, 2019
An ADMM Approach to Masked Signal Decomposition Using Subspace RepresentationShervin Minaee, Yao Wang
Sensors (Basel, Switzerland)|April 30, 2021
Deep-Emotion: Facial Expression Recognition Using Attentional Convolutional NetworkShervin Minaee, Mehdi Minaei, Amirali Abdolrashidi
Arxiv|August 9, 2020
COVID TV-UNet: Segmenting COVID-19 Chest CT Images Using Connectivity Imposed U-NetNarges Saeedizadeh, Shervin Minaee, Rahele Kafieh, et al.
Computer Methods and Programs in Biomedicine Update|August 2, 2021
COVID TV-Unet: Segmenting COVID-19 chest CT images using connectivity imposed UnetNarges Saeedizadeh, Shervin Minaee, Rahele Kafieh, et al.
Medical Image Analysis|August 12, 2020
Deep-COVID: Predicting COVID-19 from chest X-ray images using deep transfer learningShervin Minaee, Rahele Kafieh, Milan Sonka, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence|February 17, 2021
Image Segmentation Using Deep Learning: A SurveyShervin Minaee, Yuri Boykov, Fatih Porikli, et al.
IEEE Transactions on Neural Networks and Learning Systems|October 31, 2025
Multiscale Contrastive Learning for Node Clustering Based on Variational Graph Auto-EncoderNazila Pourhaji Aghayengejeh, M A Balafar, Jafar Tanha, et al.
IEEE Transactions on Medical Imaging|March 21, 2019
MTBI Identification From Diffusion MR Images Using Bag of Adversarial Visual FeaturesShervin Minaee, Yao Wang, Alp Aygar, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|November 17, 2018
A Deep Unsupervised Learning Approach Toward MTBI Identification Using Diffusion MRIShervin Minaee, Yao Wang, Anna Choromanska, et al.
Computational and Mathematical Methods in Medicine|March 8, 2021
COVID-19 in Iran: Forecasting Pandemic Using Deep LearningRahele Kafieh, Roya Arian, Narges Saeedizadeh, et al.
Pageof 1

Showing results (1-10 of 10) with videos related to

Sort By:
Pageof 1
IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society|February 1, 2019
An ADMM Approach to Masked Signal Decomposition Using Subspace RepresentationShervin Minaee, Yao Wang
Sensors (Basel, Switzerland)|April 30, 2021
Deep-Emotion: Facial Expression Recognition Using Attentional Convolutional NetworkShervin Minaee, Mehdi Minaei, Amirali Abdolrashidi
Arxiv|August 9, 2020
COVID TV-UNet: Segmenting COVID-19 Chest CT Images Using Connectivity Imposed U-NetNarges Saeedizadeh, Shervin Minaee, Rahele Kafieh, et al.
Computer Methods and Programs in Biomedicine Update|August 2, 2021
COVID TV-Unet: Segmenting COVID-19 chest CT images using connectivity imposed UnetNarges Saeedizadeh, Shervin Minaee, Rahele Kafieh, et al.
Medical Image Analysis|August 12, 2020
Deep-COVID: Predicting COVID-19 from chest X-ray images using deep transfer learningShervin Minaee, Rahele Kafieh, Milan Sonka, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence|February 17, 2021
Image Segmentation Using Deep Learning: A SurveyShervin Minaee, Yuri Boykov, Fatih Porikli, et al.
IEEE Transactions on Neural Networks and Learning Systems|October 31, 2025
Multiscale Contrastive Learning for Node Clustering Based on Variational Graph Auto-EncoderNazila Pourhaji Aghayengejeh, M A Balafar, Jafar Tanha, et al.
IEEE Transactions on Medical Imaging|March 21, 2019
MTBI Identification From Diffusion MR Images Using Bag of Adversarial Visual FeaturesShervin Minaee, Yao Wang, Alp Aygar, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|November 17, 2018
A Deep Unsupervised Learning Approach Toward MTBI Identification Using Diffusion MRIShervin Minaee, Yao Wang, Anna Choromanska, et al.
Computational and Mathematical Methods in Medicine|March 8, 2021
COVID-19 in Iran: Forecasting Pandemic Using Deep LearningRahele Kafieh, Roya Arian, Narges Saeedizadeh, et al.
Pageof 1