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20152022
most citedDeep-Emotion: Facial Expression Recognition Using Attentional Convolutional Network

85 citations · 402 across the 20 of their papers we have counts for

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23 papers · 1 filter

cs.CV202151 cited

Going Deeper Into Face Detection: A Survey

Shervin Minaee, Ping Luo, Zhe Lin +1

Face detection is a crucial first step in many facial recognition and face analysis systems. Early approaches for face detection were mainly based on classifiers built on top of ha…

cs.CV2020

Age and Gender Prediction From Face Images Using Attentional Convolutional Network

Amirali Abdolrashidi, Mehdi Minaei, Elham Azimi +1

Automatic prediction of age and gender from face images has drawn a lot of attention recently, due it is wide applications in various facial analysis problems. However, due to the…

cs.CV2020

Deep-COVID: Predicting COVID-19 From Chest X-Ray Images Using Deep Transfer Learning

Shervin Minaee, Rahele Kafieh, Milan Sonka +2

The COVID-19 pandemic is causing a major outbreak in more than 150 countries around the world, having a severe impact on the health and life of many people globally. One of the cru…

cs.CV2020

Palm-GAN: Generating Realistic Palmprint Images Using Total-Variation Regularized GAN

Shervin Minaee, Mehdi Minaei, Amirali Abdolrashidi

Generating realistic palmprint (more generally biometric) images has always been an interesting and, at the same time, challenging problem. Classical statistical models fail to gen…

cs.CV2020

Image Segmentation Using Deep Learning: A Survey

Shervin Minaee, Yuri Boykov, Fatih Porikli +3

Image segmentation is a key topic in image processing and computer vision with applications such as scene understanding, medical image analysis, robotic perception, video surveilla…

cs.CV2019

Biometrics Recognition Using Deep Learning: A Survey

Shervin Minaee, Amirali Abdolrashidi, Hang Su +2

Deep learning-based models have been very successful in achieving state-of-the-art results in many of the computer vision, speech recognition, and natural language processing tasks…