546 citations · 740 across the 23 of their papers we have counts for
3 papers · 1 filter
Quantifying the Preferential Direction of the Model Gradient in Adversarial Training With Projected Gradient Descent
Ricardo Bigolin Lanfredi, Joyce D. Schroeder, Tolga Tasdizen
Adversarial training, especially projected gradient descent (PGD), has proven to be a successful approach for improving robustness against adversarial attacks. After adversarial tr…
Interpretation of Disease Evidence for Medical Images Using Adversarial Deformation Fields
Ricardo Bigolin Lanfredi, Joyce D. Schroeder, Clement Vachet +1
The high complexity of deep learning models is associated with the difficulty of explaining what evidence they recognize as correlating with specific disease labels. This informati…
Inter-slice image augmentation based on frame interpolation for boosting medical image segmentation accuracy
Zhaotao Wu, Jia Wei, Wenguang Yuan +2
We introduce the idea of inter-slice image augmentation whereby the numbers of the medical images and the corresponding segmentation labels are increased between two consecutive im…