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Traffic Information Detection

EasyChair Preprint no. 2337, version 1

Versions: 12history
10 pagesDate: January 8, 2020


In recent years, with a number of technology breakthroughs in the world, one of the Artificial Intelligence (AI) branches self-driving vehicle is becoming closer to our lives. In this paper we built a model which contains two submodules: lane detection and vehicle detection. Our lane detection model is based on a heuristic approach to detect lanes. It can be broken down into three steps: Image preprocess, Lane edge points identification, and lane cure generation. As for the vehicle detection, we applied YOLO series algorithms which are fast, accurate and can be used in real-time detection.

Keyphrases: computer vision, deep learning, lane detection, vehicle detection

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Donghao Qiao and Jiayuan Zhou and Farhana Zulkernine},
  title = {Traffic Information Detection},
  howpublished = {EasyChair Preprint no. 2337},

  year = {EasyChair, 2020}}
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