31 citations · 33 across the 6 of their papers we have counts for
4 papers · 1 filter
Exploring Weakly Supervised Semantic Segmentation Ensembles for Medical Imaging Systems
Erik Ostrowski, Bharath Srinivas Prabakaran, Muhammad Shafique
Reliable classification and detection of certain medical conditions, in images, with state-of-the-art semantic segmentation networks, require vast amounts of pixel-wise annotation.…
ISLE: A Framework for Image Level Semantic Segmentation Ensemble
Erik Ostrowski, Muhammad Shafique
One key bottleneck of employing state-of-the-art semantic segmentation networks in the real world is the availability of training labels. Conventional semantic segmentation network…
SILOP: An Automated Framework for Semantic Segmentation Using Image Labels Based on Object Perimeters
Erik Ostrowski, Bharath Srinivas Prabakaran, Muhammad Shafique
Achieving high-quality semantic segmentation predictions using only image-level labels enables a new level of real-world applicability. Although state-of-the-art networks deliver r…
ReFit: A Framework for Refinement of Weakly Supervised Semantic Segmentation using Object Border Fitting for Medical Images
Bharath Srinivas Prabakaran, Erik Ostrowski, Muhammad Shafique
Weakly Supervised Semantic Segmentation (WSSS) relying only on image-level supervision is a promising approach to deal with the need for Segmentation networks, especially for gener…