There are 1 repository under reconstruction-algorithm topic.
High-resolution point cloud reconstruction from a compact Gaussian Mixture Model.
Reconstruction Algorithms for Compressive Sensing and Compressive Imaging
Wave optical models and inverse algorithms for label-agnostic imaging of density & orientation.
The Tomographer package implements the mathematical spatial image reconstruction of any set of read counts as described in the following article: https://www.nature.com/articles/s41587-021-00879-7
Data reconstruction and analysis tools for tomography data acquired at the P05 Imaging Beamline (IBL) and the P07 High-Energy Material Science (HEMS) beamline at PETRA III at DESY, both operated by Helmholtz-Zentrum Hereon.
DEEP-squared: Deep Learning Powered De-scattering with Excitation Patterning
UniTN Deep Learning Project 2021-22. Build a deep learning framework on a standard setting of Unsupervised Domain Adaptation (UDA).
Direct 3D mesh reconstruction from tomographic projection data
Code accompanying 'A linear method for camera pair self-calibration' paper about camera pair self-calibration and metric reconstruction starting from a projective reconstruction, assuming different and varying focal lengths
A collection of inverse problems (e.g., reconstruction of databases, algebraic reconstruction, topological derivatives, gravitational prospecting)
Deconvolution of the growth law equation. Code and replication data for https://doi.org/10.5194/gi-11-293-2022
This repository contains the official implementation of the paper "Seismic Source Recovery Algorithm via Internal Learning in the Cross-spread Domain" published by European Association of Geoscientists & Engineers
Research project exploring multiplex reconstruction techniques informed by graph embeddings.
Git Repository for the Hyperspectral Adaptive Imager (ImHypAd) in collaboration between two French laboratories, namely IRAP and LAAS and Airbus Space & Defense.
A GUI MATLAB APPLICATION FOR TOMOGRAPHY RECONSTRUCTION AND VISUALIZATION
This repository has research paper implementation which reconstructs training data.
Research project exploring multiplex reconstruction techniques informed by Naive Bayesian classifiers.
Diffuse Optical Tomography (DOT) is an non-invasive optical imaging technique that measures the optical properties of physiological tissue using near infrared spectrum light. Optical properties are extracted from the measurement using reconstruction algorithm. This project uses the steepest descent method for reconstruction of optical data.
RGBD quick reconstruction
Parametric LHCb Run 3 VELO simulation for reconstruction studies
Algorithm to reconstruct trajectories from sensor data