segger_dev
importeddata/segger-dev
a cutting-edge cell segmentation model specifically designed for single-molecule resolved spatial omics datasets. It addresses the challenge of accurately segmenting individual cells in complex…
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Data & Standards
- Subcategory
- unknown
- License
- MIT(osi)
- Status
- active
- Maturity
- deployed
- Organization
- unknown
- Country
- unknown
- Homepage
- elihei2.github.io/segger_dev/
- Repository
- github.com/EliHei2/segger_dev
- Documentation
- unknown
- Tags
- ai · cell-segmentation · graph-neural-networks · graphs · molecule-graphs · oncology · segmentation · single-cell-analysis
- 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.
- molgraphgraph-neural-networks · graphs
Graph neural networks for molecular machine learning: Implemented and compatible with TensorFlow and Keras.
- SLATgraph-neural-networks · single-cell-analysis
Spatial-Linked Alignment Tool
Network analysis and visualization of drug-drug interactions with NetworkX and Pyvis
- VIAgraphs
trajectory inference
- COSGsingle-cell-analysis
Accurate and fast cell marker gene identification with COSG
- randomlysingle-cell-analysis
A Library for Denoising Single-Cell Data with Random Matrix Theory
- api.github.com/repos/EliHei2/segger_devretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2026-05-25, 90 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/38.json→ .entries["segger-dev"]
Entries are sharded 64 ways by a stable hash of the id, so a consumer can find any record without an index.