SUPPORT
importedsoftware/support
Accurate denoising of voltage imaging data through statistically unbiased prediction, Nature Methods.
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Software & Systems
- Subcategory
- unknown
- License
- GPL-3.0(osi)
- Status
- maintained
- Maturity
- deployed
- Organization
- NICALab
- Country
- unknown
- Repository
- github.com/NICALab/SUPPORT
- Documentation
- unknown
- Tags
- calcium-imaging · deep-learning · denoising · microscopy · neural-network · self-supervised-learning · structural-imaging · time-lapse-imaging
- 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.
- DeepVIDv2denoising · microscopy · self-supervised-learning
DeepVID v2: Self-Supervised Denoising with Decoupled Spatiotemporal Enhancement for Low-Photon Voltage Imaging
- GutAnalysisToolboxcalcium-imaging · microscopy
Analysis and characterisation of cells within the gut wall using deep learning models. The current focus is on studying enteric neurons and enteric glia.
- miocalcium-imaging · microscopy
miniscope I/O sdk
- STABLEcalcium-imaging · microscopy
Preserving Spatial and Quantitative Information in Unpaired Biomedical Image-to-Image Translation
- deepinvdenoising · microscopy
DeepInverse: a PyTorch library for solving imaging inverse problems using deep learning
- eeg-self-supervisionneural-network · self-supervised-learning
Resources for the paper titled "Domain-guided Self-supervision of EEG Data Improves Downstream Classification Performance and Generalizability". Accepted at ML4H Symposium 2021 with an oral spotlight!
- api.github.com/repos/NICALab/SUPPORTretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2025-08-11, 108 stars, license reported as GPL-3.0. Category and schematic were assigned by keyword heuristics and are unreviewed.
Not yet verified by a human. Correct this record →
/v1/entries/40.json→ .entries["support"]
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