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20122022
most citedA Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges

2.7k citations · 7k across the 44 of their papers we have counts for

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Showing 2021Show all

15 papers · 1 filter

cs.RO2021★ 48 cited

Applied Exoskeleton Technology: A Comprehensive Review of Physical and Cognitive Human-Robot Interaction

Farhad Nazari, Navid Mohajer, Darius Nahavandi +2

Exoskeletons and orthoses are wearable mobile systems providing mechanical benefits to the users. Despite significant improvements in the last decades, the technology is not fully…

cs.CV2021★ 1 cited

A Comprehensive Study on Torchvision Pre-trained Models for Fine-grained Inter-species Classification

Feras Albardi, H M Dipu Kabir, Md Mahbub Islam Bhuiyan +3

This study aims to explore different pre-trained models offered in the Torchvision package which is available in the PyTorch library. And investigate their effectiveness on fine-gr…

cs.CV2021

What happens in Face during a facial expression? Using data mining techniques to analyze facial expression motion vectors

Mohamad Roshanzamir, Roohallah Alizadehsani, Mahdi Roshanzamir +4

One of the most common problems encountered in human-computer interaction is automatic facial expression recognition. Although it is easy for human observer to recognize facial exp…

eess.SP2021★ 205 cited

Automatic Diagnosis of Schizophrenia in EEG Signals Using CNN-LSTM Models

Afshin Shoeibi, Delaram Sadeghi, Parisa Moridian +8

Schizophrenia (SZ) is a mental disorder whereby due to the secretion of specific chemicals in the brain, the function of some brain regions is out of balance, leading to the lack o…

cs.CV2021★ 76 cited

MCUa: Multi-level Context and Uncertainty aware Dynamic Deep Ensemble for Breast Cancer Histology Image Classification

Zakaria Senousy, Mohammed M. Abdelsamea, Mohamed Medhat Gaber +4

Breast histology image classification is a crucial step in the early diagnosis of breast cancer. In breast pathological diagnosis, Convolutional Neural Networks (CNNs) have demonst…

cs.LG2021★ 12 cited

Uncertainty-Aware Credit Card Fraud Detection Using Deep Learning

Maryam Habibpour, Hassan Gharoun, Mohammadreza Mehdipour +7

Countless research works of deep neural networks (DNNs) in the task of credit card fraud detection have focused on improving the accuracy of point predictions and mitigating unwant…

cs.CV2021★ 1 cited

An Uncertainty-Aware Deep Learning Framework for Defect Detection in Casting Products

Maryam Habibpour, Hassan Gharoun, AmirReza Tajally +4

Defects are unavoidable in casting production owing to the complexity of the casting process. While conventional human-visual inspection of casting products is slow and unproductiv…

eess.IV2021★ 8 cited

Confidence Aware Neural Networks for Skin Cancer Detection

Donya Khaledyan, AmirReza Tajally, Ali Sarkhosh +4

Deep learning (DL) models have received particular attention in medical imaging due to their promising pattern recognition capabilities. However, Deep Neural Networks (DNNs) requir…

cs.LG2021★ 92 cited

An overview of deep learning techniques for epileptic seizures detection and prediction based on neuroimaging modalities: Methods, challenges, and future works

Afshin Shoeibi, Parisa Moridian, Marjane Khodatars +9

Epilepsy is a disorder of the brain denoted by frequent seizures. The symptoms of seizure include confusion, abnormal staring, and rapid, sudden, and uncontrollable hand movements.…

eess.IV2021★ 187 cited

Applications of Deep Learning Techniques for Automated Multiple Sclerosis Detection Using Magnetic Resonance Imaging: A Review

Afshin Shoeibi, Marjane Khodatars, Mahboobeh Jafari +9

Multiple Sclerosis (MS) is a type of brain disease which causes visual, sensory, and motor problems for people with a detrimental effect on the functioning of the nervous system. I…

cs.LG2021★ 154 cited

Time series forecasting of new cases and new deaths rate for COVID-19 using deep learning methods

Nooshin Ayoobi, Danial Sharifrazi, Roohallah Alizadehsani +9

The first known case of Coronavirus disease 2019 (COVID-19) was identified in December 2019. It has spread worldwide, leading to an ongoing pandemic, imposed restrictions and costs…

cs.CV2021★ 115 cited

Combining a Convolutional Neural Network with Autoencoders to Predict the Survival Chance of COVID-19 Patients

Fahime Khozeimeh, Danial Sharifrazi, Navid Hoseini Izadi +10

COVID-19 has caused many deaths worldwide. The automation of the diagnosis of this virus is highly desired. Convolutional neural networks (CNNs) have shown outstanding classificati…

cs.LG2021★ 170 cited

An overview of artificial intelligence techniques for diagnosis of Schizophrenia based on magnetic resonance imaging modalities: Methods, challenges, and future works

Delaram Sadeghi, Afshin Shoeibi, Navid Ghassemi +9

Schizophrenia (SZ) is a mental disorder that typically emerges in late adolescence or early adulthood. It reduces the life expectancy of patients by 15 years. Abnormal behavior, pe…

eess.IV2021

Fusion of convolution neural network, support vector machine and Sobel filter for accurate detection of COVID-19 patients using X-ray images

Danial Sharifrazi, Roohallah Alizadehsani, Mohamad Roshanzamir +13

The coronavirus (COVID-19) is currently the most common contagious disease which is prevalent all over the world. The main challenge of this disease is the primary diagnosis to pre…

eess.IV2021★ 20 cited

Uncertainty-Aware Semi-Supervised Method Using Large Unlabeled and Limited Labeled COVID-19 Data

Roohallah Alizadehsani, Danial Sharifrazi, Navid Hoseini Izadi +11

The new coronavirus has caused more than one million deaths and continues to spread rapidly. This virus targets the lungs, causing respiratory distress which can be mild or severe.…