quanfima
Data analyzer
A collection of useful functions for morphological analysis and visualization of 2D/3D data from various areas of material science.
Quanfima (Quantitative Analysis of Fibrous Materials)
28 stars
2 watching
16 forks
Language: Python
last commit: about 1 year ago
Linked from 1 awesome list
data-analysismaterial-sciencemorphological-analysisvolumetric-data
Related projects:
Repository | Description | Stars |
---|---|---|
| An R package for natural language processing and text analysis. | 847 |
| A Python library for analyzing and visualizing data from various aerosol sizing instruments | 34 |
| Analyzes single cell RNA sequence data with quantitative phenotypes | 13 |
| A Python package for analyzing high-throughput single-cell imaging data | 5 |
| A software tool for analyzing single-cell regulome data from ATAC-seq experiments. | 13 |
| A Python-based deep learning project for medical image analysis, specifically focused on detecting RSNA intracranial hemorrhage. | 41 |
| An implementation of a method for analyzing high-dimensional datasets by decomposing correlations between multiple variables. | 11 |
| Analyze fiber orientation and intensity around cells in 3D fiber matrices to quantify cellular forces. | 8 |
| An object-oriented Python library for analyzing single-cell RNA-seq data using topological representations | 7 |
| A MATLAB toolbox for analyzing resting-state functional MRI data by estimating and deconvolving the hemodynamic response function. | 48 |
| A software framework for learning spatial embeddings from high-dimensional transcriptomics data using an adaptive graph attention auto-encoder | 41 |
| A tool for analyzing and visualizing bathymetric and topographic data using R. | 32 |
| Analyzes single-cell multi-omics data from various modalities like RNA-seq and ATAC-seq | 16 |
| An implementation of a multi-task deep morphological analyzer with neural models and post-processing tools for natural language processing tasks. | 1 |
| An R-based web application for guided single-cell RNA-seq data analysis and clustering | 33 |