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ImaadHasan2002/Road-Segmentation-Object-Detection-using-Deep-Learning

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In this project, a deep learning-based approach is used for lane detection on semi-urban roads. The proposed model consists of two main components: a CNN architecture, ResNet101, for semantic segmentation to accurately detect and classify road features, and YOLOv8 for object detection.

active 2023-11-102024-08-06 (UTC)

Complete coverage26,776 / 26,776 hourly files (100%) · 2 absent upstream2023-08-152026-09-03 (UTC)
Events
74
Pushes
61
Pull requests
0
Issues
2
Stars
5
Forks
1

Activity over time

Daily event counts in the loaded window

Line chart, 271 days from 2023-11-10 to 2024-08-06. Pushes: 61 total, peak 61 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 2 total, peak 1 in a day. Comments: 2 total, peak 1 in a day. Stars: 5 total, peak 2 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
ImaadHasan2002626101
JingYuchen93001

Recent activity

Latest issues, pull requests and releases

  • Issue comment#1JingYuchen92024-07-08 04:38
    question about yolov8
  • Issue#1JingYuchen92024-07-08 04:38
    question about yolov8
  • Issue comment#1ImaadHasan20022024-07-07 05:56
    question about yolov8
  • Issue#1JingYuchen92024-06-28 11:01
    question about yolov8

Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 5 stars here means stars gained during the window, not the repo's star count.