Singanallur Venkatakrishnan R&D Staff Contact VENKATAKRISV@ORNL.GOV All Publications 2.5D Super-Resolution Approaches for X-Ray Computed Tomography-Based Inspection of Additively Manufactured Parts A Learnt Half-Quadratic Splitting-Based Algorithm for Fast and High-Quality Industrial Cone-beam CT Reconstruction A machine learning decision criterion for reducing scan time for hyperspectral neutron computed tomography systems Oak Ridge National Laboratory's Strategic Research and Development Insights for Digital Twins Deep Learning Based Workflow for Accelerated Industrial X-Ray Computed Tomography Neural network-based single material beam-hardening correction for X-ray CT in Additive Manufacturing Reducing Artifacts in BF and HAADF-STEM Images of Pt/C Fuel Cells using MBIR-ARAR An Edge Alignment-Based Orientation Selection Method for Neutron Tomography Validating the Use of Gaussian Process Regression for Adaptive Mapping of Residual Stress Fields Enabling rapid X-ray CT characterisation for additive manufacturing using CAD models and deep learning-based reconstruction Adaptive sampling for accelerating neutron diffraction-based strain mapping* Physics guided machine learning for multi-material decomposition of tissues from dual-energy CT scans of simulated breast models with calcifications What does it take to “see” air leakage through a building envelope?... Simurgh: A Framework for Cad-Driven Deep Learning Based X-Ray CT Reconstruction Application of reference-free natural background–oriented schlieren photography for visualizing leakage sites in building walls High Throughput Deep Learning-Based X-ray CT Characterization for Process Optimization in Metal Additive Manufacturing Model-Based Reconstruction for Collimated Beam Ultrasound Systems Model-based reconstruction for enhanced x-ray CT of dense tri-structural isotropic particles Algorithm-Driven Advances for Scientific CT Instruments: From model-based to deep learning-based approaches High Resolution X-Ray CT Reconstruction of Additively Manufactured Metal Parts using Generative Adversarial Network-based Domain Adaptation in AI-CT Convolutional Neural Network Based Non-Iterative Reconstruction for Accelerating NeutronTomography Convolutional neural network based non-iterative reconstruction for accelerating neutron tomography * Improved Acquisition and Reconstruction for Wavelength-Resolved Neutron Tomography Beam Hardening Artifact Reduction in X-Ray CT Reconstruction of 3D Printed Metal Parts Leveraging Deep Learning and CAD Model... Model-based Reconstruction for Single Particle Cryo-Electron Microscopy Pagination Current page 1 Page 2 Next page ›› Last page Last » Key Links ORCID Organizations Energy Science and Technology Directorate Electrification and Energy Infrastructures Division Energy Sensing, Analytics and Communications Section Multimodal Sensor Analytics Group Electrification Section
