192 citations · 729 across the 35 of their papers we have counts for
8 papers · 2 filters
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…
Deep Learning Models for Digital Pathology
Aïcha BenTaieb, Ghassan Hamarneh
Histopathology images; microscopy images of stained tissue biopsies contain fundamental prognostic information that forms the foundation of pathological analysis and diagnostic med…
Deep Semantic Segmentation of Natural and Medical Images: A Review
Saeid Asgari Taghanaki, Kumar Abhishek, Joseph Paul Cohen +2
The semantic image segmentation task consists of classifying each pixel of an image into an instance, where each instance corresponds to a class. This task is a part of the concept…
Visual Diagnosis of Dermatological Disorders: Human and Machine Performance
Jeremy Kawahara, Ghassan Hamarneh
Skin conditions are a global health concern, ranking the fourth highest cause of nonfatal disease burden when measured as years lost due to disability. As diagnosing, or classifyin…
Learning to Segment Skin Lesions from Noisy Annotations
Zahra Mirikharaji, Yiqi Yan, Ghassan Hamarneh
Deep convolutional neural networks have driven substantial advancements in the automatic understanding of images. Requiring a large collection of images and their associated annota…
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…