activity
20172025
most citedVisual Analytics for Explainable and Trustworthy Artificial Intelligence

6 citations · 13 across the 7 of their papers we have counts for

collaborators

7 papers

cs.HC2025★ 6 cited

Visual Analytics for Explainable and Trustworthy Artificial Intelligence

Angelos Chatzimparmpas

Our society increasingly depends on intelligent systems to solve complex problems, ranging from recommender systems suggesting the next movie to watch to AI models assisting in med…

cs.CV2024★ 4 cited

Efficient Neural Representation of Volumetric Data using Coordinate-Based Networks

Sudarshan Devkota, Sumanta Pattanaik

In this paper, we propose an efficient approach for the compression and representation of volumetric data utilizing coordinate-based networks and multi-resolution hash encoding. Ef…

cs.CV2022

Reference Based Color Transfer for Medical Volume Rendering

Sudarshan Devkota, Summanta Pattanaik

The benefits of medical imaging are enormous. Medical images provide considerable amounts of anatomical information and this facilitates medical practitioners in performing effecti…

cs.GR2022

Deep Learning based Super-Resolution for Medical Volume Visualization with Direct Volume Rendering

Sudarshan Devkota, Sumanta Pattanaik

Modern-day display systems demand high-quality rendering. However, rendering at higher resolution requires a large number of data samples and is computationally expensive. Recent a…

cs.GR2022

Interpretable Disentangled Parametrization of Measured BRDF with -VAE

Alexis Benamira, Sachin Shah, Sumanta Pattanaik

Finding a low dimensional parametric representation of measured BRDF remains challenging. Currently available solutions are either not interpretable, or rely on limited analytical…

cs.GR2017

GPU accelerated computation of Polarized Subsurface BRDF for Flat Particulate Layers

Charly Collin, Sumanta Pattanaik

BRDF of most real world materials has two components, the surface BRDF due to the light reflecting at the surface of the material and the subsurface BRDF due to the light entering…

cs.CV2017★ 3 cited

Robust and fully automated segmentation of mandible from CT scans

Neslisah Torosdagli, Denise K. Liberton, Payal Verma +3

Mandible bone segmentation from computed tomography (CT) scans is challenging due to mandible's structural irregularities, complex shape patterns, and lack of contrast in joints. F…