amfinder
importedsoftware/amfinder
The Automatic Mycorrhiza Finder (AMFinder) allows for automatic computer vision-based identification and quantification of AM fungal colonisation and intraradical hyphal structures on ink-stained…
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Software & Systems
- Subcategory
- unknown
- License
- MIT(osi)
- Status
- dormant
- Maturity
- deployed
- Organization
- unknown
- Country
- unknown
- Homepage
- unknown
- Repository
- github.com/SchornacklabSLCU/amfinder
- Documentation
- unknown
- Tags
- deep-learning · gtk2 · image-analysis · keras · microscopy · mycorrhiza · neural-networks · ocaml
- Regulatory
- unknown
Top contributors by commit count, from the project’s public repository. Avatars are served by their origin, not stored here. To be removed from this list, open an issue.
Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.
- cellfinderimage-analysis · microscopy
Automated 3D cell detection in very large images
- ExTrackimage-analysis · microscopy
ExTrack MLE for diffusive noisy single-particle tracks
- frcimage-analysis · microscopy
frc is a Python package for computing the Fourier Ring Correlation (FRC) of images using DIPlib
- imaris_extensionsimage-analysis · microscopy
Algorithmic and Utility Extensions for the Imaris Program
- mcmicroimage-analysis · microscopy
An end-to-end processing pipeline that transforms multi-channel whole-slide images into single-cell data.
- merfish3d-analysisimage-analysis · microscopy
GPU accelerated post-processing for 2D or 3D imaging spatial transcriptomics data.
- api.github.com/repos/SchornacklabSLCU/amfinderretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2023-11-03, 27 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.
Not yet verified by a human. Correct this record →
/v1/entries/39.json→ .entries["amfinder"]
Entries are sharded 64 ways by a stable hash of the id, so a consumer can find any record without an index.