Corpus ID: 210956306

Traffic Information Detection

@inproceedings{Qiao2020TrafficID,
  title={Traffic Information Detection},
  author={Donghao Qiao and Jiayuan Zhou and Farhana H. Zulkernine},
  year={2020}
}
  • Donghao Qiao, Jiayuan Zhou, Farhana H. Zulkernine
  • Published 2020
  • Computer Science
  • 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. 

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    References

    Publications referenced by this paper.
    SHOWING 1-4 OF 4 REFERENCES

    YOLO9000: Better, Faster, Stronger

    VIEW 5 EXCERPTS
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    You Only Look Once: Unified, Real-Time Object Detection