A Transfer Learning Based Active Learning Framework for Brain Tumor Classification

no code implementations • 16 Nov 2020 • Ruqian Hao, Khashayar Namdar, Lin Liu, Farzad Khalvati

The model achieved AUC of 82% compared with AUC of 78. 48% for the baseline, which reassures the robustness and stability of our proposed transfer learning augmented with active learning framework while significantly reducing the size of training data.

Active Learning General Classification +1

A Comprehensive Study of Data Augmentation Strategies for Prostate Cancer Detection in Diffusion-weighted MRI using Convolutional Neural Networks

no code implementations • 1 Jun 2020 • Ruqian Hao, Khashayar Namdar, Lin Liu, Masoom A. Haider, Farzad Khalvati

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 true distribution.

Data Augmentation