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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…
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…
Accurate Prediction Using Triangular Type-2 Fuzzy Linear Regression
Assef Zare, Afshin Shoeibi, Narges Shafaei +4
Many works have been done to handle the uncertainties in the data using type 1 fuzzy regression. Few type 2 fuzzy regression works used interval type 2 for indeterminate modeling u…
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…
Detection of Epileptic Seizures on EEG Signals Using ANFIS Classifier, Autoencoders and Fuzzy Entropies
Afshin Shoeibi, Navid Ghassemi, Marjane Khodatars +7
Epileptic seizures are one of the most crucial neurological disorders, and their early diagnosis will help the clinicians to provide accurate treatment for the patients. The electr…
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…
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…
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…
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…
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.…
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…
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…
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…
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.…