human-against-machine
importedsoftware/human-against-machine
Deep learning on dermatoscopic images, with a browser demo that lets you try the task against the model.
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Software & Systems
- Subcategory
- unknown
- License
- MIT(osi)
- Status
- active
- Maturity
- deployed
- Organization
- unknown
- Country
- unknown
- Documentation
- unknown
- Tags
- computer-vision · deep-learning · dermatology · machine-learning · melanoma · onnx · pytorch-cnn · quarto
- 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.
- bh-sentinelonnx
Open-source clinical safety signal detection for behavioral health systems. Text in. Flags out. Clinician decides.
- learn-r-with-aiquarto
Learn R statistics for clinical research with AI assistance—interactive Quarto tutorial from zero programming knowledge to publication-ready biostatistics analysis.
- r-notesquarto
R语言学习笔记——从数据清洗到高级统计学和生物信息学
- survival-pipequarto
R pipeline for survival analysis with automatic detection of competing risks, recurrent events, time-varying exposures, and clustering—routes to appropriate statistical methods and generates…
- dermwatchcomputer-vision · dermatology
Private local skin-photo journal for tracking visible change — not a skin-cancer diagnostic tool
- realesrgan-mobilecomputer-vision · dermatology
Real-ESRGAN model deployed on Android using NCNN (C++/JNI) and ExecuTorch (Java) for real-time image super-resolution in dermatology, with reproducible benchmarking (PSNR, SSIM, MSE, LPIPS).
- api.github.com/repos/tmfreiberg/human-against-machineretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2026-08-05, 4 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/36.json→ .entries["human-against-machine"]
Entries are sharded 64 ways by a stable hash of the id, so a consumer can find any record without an index.