Semi_Supervised_Medical_Image_Classification Muzammil592 · COMPLETED
Engineered a FixMatch-based computer vision model achieving 88% accuracy using only 10% labeled data. Implemented pseudo-labeling, weak/strong consistency regularization, and an interactive Gradio app. Demonstrates scalable learning on low-annotation datasets.
github.com/Muzammil592/Semi_Supervised_Medical_Image_Classification · ★ 1 · Forks 0 · Size 56 KB
SUMMARY
Technologies 5
Scored 5
Observed 5
Practices 6
Evidence 6
Skips 0
COVERAGE
Analyzed 18 files · 11 commits · 0 API calls
TECHNOLOGIES & DEPTH
Markdown LANGUAGE Depth 70
1 files · PRODUCTION
Python LANGUAGE Depth 70
16 files · PRODUCTION
pip BUILD_TOOL Depth 80
1 files · CONFIGURATION
NumPy LIBRARY Depth 66
4 files · PRODUCTION
pandas LIBRARY Depth 70
10 files · PRODUCTION
PRACTICES
documentation · observedautomated_tests · absentcontinuous_integration · absentcontainerization · absentlinting · absentformatting · absent
ACTIVITY & OWNERSHIP
First commit 2026-09-17
Last commit 2026-09-24
Active months 1
Commits 11