2 citations · 3 across the 3 of their papers we have counts for
6 papers
Signed Input Regularization
Saeid Asgari Taghanaki, Kumar Abhishek, Ghassan Hamarneh
Over-parameterized deep models usually over-fit to a given training distribution, which makes them sensitive to small changes and out-of-distribution samples at inference time, lea…
Artificial Intelligence in Glioma Imaging: Challenges and Advances
Weina Jin, Mostafa Fatehi, Kumar Abhishek +3
Primary brain tumors including gliomas continue to pose significant management challenges to clinicians. While the presentation, the pathology, and the clinical course of these les…
Mask2Lesion: Mask-Constrained Adversarial Skin Lesion Image Synthesis
Kumar Abhishek, Ghassan Hamarneh
Skin lesion segmentation is a vital task in skin cancer diagnosis and further treatment. Although deep learning based approaches have significantly improved the segmentation accura…
Improved Inference via Deep Input Transfer
Saied Asgari Taghanaki, Kumar Abhishek, Ghassan Hamarneh
Although numerous improvements have been made in the field of image segmentation using convolutional neural networks, the majority of these improvements rely on training with large…
A Kernelized Manifold Mapping to Diminish the Effect of Adversarial Perturbations
Saeid Asgari Taghanaki, Kumar Abhishek, Shekoofeh Azizi +1
The linear and non-flexible nature of deep convolutional models makes them vulnerable to carefully crafted adversarial perturbations. To tackle this problem, we propose a non-linea…
Summarization and Visualization of Large Volumes of Broadcast Video Data
Kumar Abhishek, Ashok Yogi
Over the past few years, there has been an astounding growth in the number of news channels as well as the amount of broadcast news video data. As a result, it is imperative that a…