Objective Evaluation of Deep Uncertainty Predictions for COVID-19 Detection. - Hamzeh Asgharnezhad; Afshar Shamsi Jokandan; Roohallah Alizadehsani; Abbas Khosravi; Saeid Nahavandi; Zahra Alizadeh Sani; Dipti Srinivasan (CoRR, 2020)

Confidence Aware Neural Networks for Skin Cancer Detection. - Donya Khaledyan; AmirReza Tajally; Ali Sarkhosh; Afshar Shamsi Jokandan; Hamzeh Asgharnezhad; Abbas Khosravi; Saeid Nahavandi (CoRR, 2021)

An Uncertainty-Aware Deep Learning Framework for Defect Detection in Casting Products. - Maryam Habibpour; Hassan Gharoun; AmirReza Tajally; Afshar Shamsi Jokandan; Hamzeh Asgharnezhad; Abbas Khosravi; Saeid Nahavandi (CoRR, 2021)

Uncertainty-Aware Credit Card Fraud Detection Using Deep Learning. - Maryam Habibpour; Hassan Gharoun; Mohammadreza Mehdipour; AmirReza Tajally; Hamzeh Asgharnezhad; Afshar Shamsi Jokandan; Abbas Khosravi; Miadreza Shafie-Khah; Saeid Nahavandi; João P. S. Catalão (CoRR, 2021)

Improving MC-Dropout Uncertainty Estimates with Calibration Error-based Optimization. - Afshar Shamsi Jokandan; Hamzeh Asgharnezhad; Moloud Abdar; AmirReza Tajally; Abbas Khosravi; Saeid Nahavandi; Henry Leung (CoRR, 2021)

An Uncertainty-Aware Transfer Learning-Based Framework for COVID-19 Diagnosis. - Afshar Shamsi Jokandan; Hamzeh Asgharnezhad; Shirin Shamsi Jokandan; Abbas Khosravi; Parham M. Kebria; Darius Nahavandi; Saeid Nahavandi; Dipti Srinivasan (IEEE Trans. Neural Networks Learn. Syst., 2021)

Improving PPG Signal Classification with Machine Learning: The Power of a Second Opinion. - Hamzeh Asgharnezhad; Afshar Shamsi Jokandan; Ivan Bakhshayeshi; Roohallah Alizadehsani; Somayyeh Chamaani; Hamid Alinejad-Rokny (DSP, 2023)

Uncertainty-aware credit card fraud detection using deep learning. - Maryam Habibpour; Hassan Gharoun; Mohammadreza Mehdipour; AmirReza Tajally; Hamzeh Asgharnezhad; Afshar Shamsi Jokandan; Abbas Khosravi; Saeid Nahavandi (Eng. Appl. Artif. Intell., 2023)

A novel uncertainty-aware deep learning technique with an application on skin cancer diagnosis. - Afshar Shamsi Jokandan; Hamzeh Asgharnezhad; Ziba Bouchani; Khadijeh Jahanian; Morteza Saberi; Xianzhi Wang 001; Imran Razzak; Roohallah Alizadehsani; Arash Mohammadi 001; Hamid Alinejad-Rokny (Neural Comput. Appl., 2023)

Enhancing Monte Carlo Dropout Performance for Uncertainty Quantification. - Hamzeh Asgharnezhad; Afshar Shamsi; Roohallah Alizadehsani; Arash Mohammadi 001; Hamid Alinejad-Rokny (CoRR, 2025)

Uncertainty-Aware Deep Learning for Automated Skin Cancer Classification: A Comprehensive Evaluation. - Hamzeh Asgharnezhad; Pegah Tabarisaadi; Abbas Khosravi; Roohallah Alizadehsani; U. Rajendra Acharya (CoRR, 2025)