A cross-platform, open-source library for the analysis of X-ray diffraction data.
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Updated
Sep 7, 2024 - Python
A cross-platform, open-source library for the analysis of X-ray diffraction data.
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.
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
Wave optical models and inverse algorithms for label-agnostic imaging of density & orientation.
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
High-resolution point cloud reconstruction from a compact Gaussian Mixture Model.
This repository has research paper implementation which reconstructs training data.
Direct 3D mesh reconstruction from tomographic projection data
Reconstruction Algorithms for Compressive Sensing and Compressive Imaging
DEEP-squared: Deep Learning Powered De-scattering with Excitation Patterning
공부 내용, 논문 번역, 책 번역
Git Repository for the Hyperspectral Adaptive Imager (ImHypAd) in collaboration between two French laboratories, namely IRAP and LAAS and Airbus Space & Defense.
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.
Scripts and analysis for the Giurgiu et al. 2024. Genome Research. "Reconstructing extrachromosomal DNA structural heterogeneity from long-read sequencing data using Decoil".
Deconvolution of the growth law equation. Code and replication data for https://doi.org/10.5194/gi-11-293-2022
A collection of inverse problems (e.g., reconstruction of databases, algebraic reconstruction, topological derivatives, gravitational prospecting)
Research project exploring multiplex reconstruction techniques informed by Naive Bayesian classifiers.
UniTN Deep Learning Project 2021-22. Build a deep learning framework on a standard setting of Unsupervised Domain Adaptation (UDA).
Research project exploring multiplex reconstruction techniques informed by graph embeddings.
An origin ensemble algorithm for Compton camera reconstruction.
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