optic-nerve-cnn
importedsoftware/optic-nerve-cnn
Code repository for a paper "Optic Disc and Cup Segmentation Methods for Glaucoma Detection with Modification of U-Net Convolutional Neural Network"
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/seva100/optic-nerve-cnn
- Documentation
- unknown
- Tags
- computer-vision · cup-segmentation-methods · glaucoma-detection · ipynb · medical-imaging · optic-disc · paper
- 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.
- paperscomputer-vision · medical-imaging · paper
Summaries of machine learning papers
- IRS_normalizationipynb
An exploration of internal reference scaling (IRS) normalization in isobaric tagging proteomics experiments.
Examples of TMT data analyses using R. Links to notebooks and repositories. Also a few spectral counting analyses.
- facemindcomputer-vision · paper
application uses computer vision and machine learning to analyze mental health based on facial expressions. The app includes login system, and real-time mental health analysis through facial…
- All-About-the-GANmedical-imaging · paper
All About the GANs(Generative Adversarial Networks) - Summarized lists for GAN
- angiodysplasia-segmentationcomputer-vision · medical-imaging
Wining solution and its further development for MICCAI 2017 Endoscopic Vision Challenge Angiodysplasia Detection and Localization
- api.github.com/repos/seva100/optic-nerve-cnnretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2022-02-28, 129 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["optic-nerve-cnn"]
Entries are sharded 64 ways by a stable hash of the id, so a consumer can find any record without an index.