30 papers
Lighting-aware Unified Model for Instance Segmentation
Qisai Liu, Alloy Das, Zhanhong Jiang +4
Foundation models like the Segment Anything Model (SAM) demonstrate impressive zero-shot generalization but frequently degrade under diverse real-world illumination, particularly f…
Neural-Network-based Viscosity Closure for Non-Newtonian Multiphase Flows
Suresh Murugaiyan, Claire L. Nelson, Dhruv Gamdha +11
Materials used in polymer-based additive manufacturing processes, such as Digital Light Processing (DLP) and direct ink writing (DIW), typically exhibit non-Newtonian rheology. Car…
GENIE: Gram-Eigenmode INR Editing with Closed-Form Geometry Updates
Samundra Karki, Adarsh Krishnamurthy, Baskar Ganapathysubramanian
Implicit Neural Representations (INRs) provide compact models of geometry, but it is unclear when their learned shapes can be edited without retraining. We show that the Gram opera…
HS-3D-NeRF: 3D Surface and Hyperspectral Reconstruction From Stationary Hyperspectral Images Using Multi-Channel NeRFs
Kibon Ku, Talukder Z. Jubery, Adarsh Krishnamurthy +1
Advances in hyperspectral imaging (HSI) and 3D reconstruction have enabled accurate, high-throughput characterization of agricultural produce quality and plant phenotypes, both ess…
Artifact Removal and Image Restoration in AFM:A Structured Mask-Guided Directional Inpainting Approach
Juntao Zhang, Angona Biswas, Jaydeep Rade +5
Atomic Force Microscopy (AFM) enables high-resolution surface imaging at the nanoscale, yet the output is often degraded by artifacts introduced by environmental noise, scanning im…
Neural Geometry for PDEs: Regularity, Stability, and Convergence Guarantees
Samundra Karki, Adarsh Krishnamurthy, Baskar Ganapathysubramanian
Implicit Neural Representations (INRs) have emerged as a powerful tool for geometric representation, yet their suitability for physics-based simulation remains underexplored. While…