activity
20182026
most citedApproxFPGAs: Embracing ASIC-Based Approximate Arithmetic Components for FPGA-Based Systems

32 citations · 117 across the 13 of their papers we have counts for

collaborators

13 papers

cs.CV2026

Benchmarking Vision-Language Models for Automated Pathology Diagnosis and Report Generation

Yumi Lee, Harim Oh, Hyoryung Kim +52

The rapid advancement of vision-language models (VLMs) has accelerated progress in computational pathology; however, whole-slide image (WSI)-based pathology report generation remai…

cs.CV2023★ 1 cited

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.…

cs.LG2023★ 11 cited

UnbiasedNets: A Dataset Diversification Framework for Robustness Bias Alleviation in Neural Networks

Mahum Naseer, Bharath Srinivas Prabakaran, Osman Hasan +1

Performance of trained neural network (NN) models, in terms of testing accuracy, has improved remarkably over the past several years, especially with the advent of deep learning. H…

cs.CV2023★ 1 cited

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…

cs.CV2023

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…

eess.IV2023★ 31 cited

FPUS23: An Ultrasound Fetus Phantom Dataset with Deep Neural Network Evaluations for Fetus Orientations, Fetal Planes, and Anatomical Features

Bharath Srinivas Prabakaran, Paul Hamelmann, Erik Ostrowski +1

Ultrasound imaging is one of the most prominent technologies to evaluate the growth, progression, and overall health of a fetus during its gestation. However, the interpretation of…