183 citations · 209 across the 9 of their papers we have counts for
10 papers
NeuroStrata: An Electroencephalographic Connectivity-Aware Deep Representation Learning Framework for Dynamic Brain Network Analysis of Mental Stress
Sayantan Acharya, Hamzeh Asgharnezhad, Abbas Khosravi +3
This study introduces NeuroStrata, a connectivity-aware deep representation learning framework for EEG-based mental stress analysis using Time-Varying Partial Directed Coherence (T…
UCTECG-Net: Uncertainty-aware Convolution Transformer ECG Network for Arrhythmia Detection
Hamzeh Asgharnezhad, Pegah Tabarisaadi, Abbas Khosravi +2
Deep learning has improved automated electrocardiogram (ECG) classification, but limited insight into prediction reliability hinders its use in safety-critical settings. This paper…
A Quad-Step Approach to Uncertainty-Aware Deep Learning for Skin Cancer Classification
Hamzeh Asgharnezhad, Pegah Tabarisaadi, Abbas Khosravi +2
Accurate skin cancer diagnosis is vital for early treatment and improved patient outcomes. Deep learning (DL) models have shown promise in automating skin cancer classification, ye…
Enhancing Monte Carlo Dropout Performance for Uncertainty Quantification
Hamzeh Asgharnezhad, Afshar Shamsi, Roohallah Alizadehsani +2
Knowing the uncertainty associated with the output of a deep neural network is of paramount importance in making trustworthy decisions, particularly in high-stakes fields like medi…
An Uncertainty-aware Loss Function for Training Neural Networks with Calibrated Predictions
Afshar Shamsi, Hamzeh Asgharnezhad, AmirReza Tajally +2
Uncertainty quantification of machine learning and deep learning methods plays an important role in enhancing trust to the obtained result. In recent years, a numerous number of un…
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…
Objective Evaluation of Deep Uncertainty Predictions for COVID-19 Detection
Hamzeh Asgharnezhad, Afshar Shamsi, Roohallah Alizadehsani +4
Deep neural networks (DNNs) have been widely applied for detecting COVID-19 in medical images. Existing studies mainly apply transfer learning and other data representation strateg…
An Uncertainty-aware Transfer Learning-based Framework for Covid-19 Diagnosis
Afshar Shamsi Jokandan, Hamzeh Asgharnezhad, Shirin Shamsi Jokandan +5
The early and reliable detection of COVID-19 infected patients is essential to prevent and limit its outbreak. The PCR tests for COVID-19 detection are not available in many countr…