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pippodima/HumanActivityRecognition

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This repository focuses on classifying human activities—such as sitting, running, and standing—using a Long Short-Term Memory (LSTM) model. The classification is based on data collected from accelerometers, gyroscopes, and other sensors embedded in both smartphones and smartwatches

active 2025-02-25 → 2025-03-04 (UTC)

Complete coverage27,789 / 27,789 hourly files (100%) · 2 absent upstream2023-08-15 → 2026-10-15 (UTC)
Events
11
Pushes
9
Pull requests
0
Issues
0
Stars
0
Forks
0

Activity over time

Daily event counts in the loaded window

Line chart, 8 days from 2025-02-25 to 2025-03-04. Pushes: 9 total, peak 4 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 0 total, peak 0 in a day. Comments: 0 total, peak 0 in a day. Stars: 0 total, peak 0 in a day.

  • Pushes
  • Pull requests
  • Issues
  • Comments
  • Stars

Top contributors

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

ContributorContributionsPushesPRsComments
pippodima9900

Recent activity

Latest issues, pull requests and releases

No issue or PR events — this repo's activity is pushes only.

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.