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Osman-Geomatics93/crop-classification-deep-learning

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Multi-class crop classification in Elgabel Region, Sudan using Sentinel-2 imagery with scikit-learn (MLP, XGBoost, Random Forest) and PyTorch deep learning (CNN1D, Hybrid CNN+MLP, Transformer). Achieves 100% accuracy with FocalLoss, SMOTE, and class weighting.

active 2026-01-292026-01-29 (UTC)

Complete coverage27,230 / 27,232 hourly files (100%) · 2 absent upstream2023-08-152026-09-22 (UTC)
Events
10
Pushes
4
Pull requests
2
Issues
0
Stars
0
Forks
0

Activity over time

Daily event counts in the loaded window

Line chart, 1 days from 2026-01-29 to 2026-01-29. Pushes: 4 total, peak 4 in a day. Pull requests: 2 total, peak 2 in a day. Issues: 0 total, peak 0 in a day. Comments: 1 total, peak 1 in a day. Stars: 0 total, peak 0 in a day.

  • Pushes
  • Pull requests
  • Issues
  • Comments
  • Stars

Stars, PRs, issues and forks are under-captured in the later part of this window. GH Archive progressively stopped capturing non-push events during 2026 — −95% or worse by the end of the window. Every series here except Pushes fades for that reason, so a decline above reflects the archive, not this repository. Pushes stay reliable throughout, so read them, and the contributor counts derived from them, as the real signal. Data health has the measurements.

Top contributors

Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity

ContributorContributionsPushesPRsComments
Osman-Geomatics934400
dependabot[bot]3021

Recent activity

Latest issues, pull requests and releases

Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 0 stars here means stars gained during the window, not the repo's star count.