211 citations · 415 across the 41 of their papers we have counts for
7 papers · 1 filter
A Transfer Learning Based Active Learning Framework for Brain Tumor Classification
Ruqian Hao, Khashayar Namdar, Lin Liu +1
Brain tumor is one of the leading causes of cancer-related death globally among children and adults. Precise classification of brain tumor grade (low-grade and high-grade glioma) a…
RANDGAN: Randomized Generative Adversarial Network for Detection of COVID-19 in Chest X-ray
Saman Motamed, Patrik Rogalla, Farzad Khalvati
COVID-19 spread across the globe at an immense rate has left healthcare systems incapacitated to diagnose and test patients at the needed rate. Studies have shown promising results…
Evaluating Knowledge Transfer in Neural Network for Medical Images
Sina Akbarian, Laleh Seyyed-Kalantari, Farzad Khalvati +1
Deep learning and knowledge transfer techniques have permeated the field of medical imaging and are considered as key approaches for revolutionizing diagnostic imaging practices. H…
A Brief Review of Deep Multi-task Learning and Auxiliary Task Learning
Partoo Vafaeikia, Khashayar Namdar, Farzad Khalvati
Multi-task learning (MTL) optimizes several learning tasks simultaneously and leverages their shared information to improve generalization and the prediction of the model for each…
A Modified AUC for Training Convolutional Neural Networks: Taking Confidence into Account
Khashayar Namdar, Masoom A. Haider, Farzad Khalvati
Receiver operating characteristic (ROC) curve is an informative tool in binary classification and Area Under ROC Curve (AUC) is a popular metric for reporting performance of binary…
Data Augmentation using Generative Adversarial Networks (GANs) for GAN-based Detection of Pneumonia and COVID-19 in Chest X-ray Images
Saman Motamed, Patrik Rogalla, Farzad Khalvati
Successful training of convolutional neural networks (CNNs) requires a substantial amount of data. With small datasets networks generalize poorly. Data Augmentation techniques impr…
A Comprehensive Study of Data Augmentation Strategies for Prostate Cancer Detection in Diffusion-weighted MRI using Convolutional Neural Networks
Ruqian Hao, Khashayar Namdar, Lin Liu +2
Data augmentation refers to a group of techniques whose goal is to battle limited amount of available data to improve model generalization and push sample distribution toward the t…