A Study on Neural Networks used for Traffic Signal Classification

@article{1703982,
      author = {Aditya Kulkarni, Omkar Hase, Hetavi Gandhi, Asst. Prof. Kopal Gangrade, Asst. Prof. Shweta Shah},
      title = {A Study on Neural Networks used for Traffic Signal Classification},
      journal = {Iconic Research And Engineering Journals},
      year = {2023},
      volume = {6},
      number = {7},
      pages = {24-29},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1703982.pdf},
      abstract = {Traffic Recognition System (TRS) plays a key role in saving millions of lives every year.It recognizes the signs placed beside the road. Many a times such signs are partially covered leading to confusion. The TRS enables the drivers to identify these signs beforehand which in turn decreases the chances of an accident occurring. Technology behind the TRS has evolved over the years and Neural Networks (CNN) has been on the forefront of this evolution. CNN models are specifically used for object detection and are widely used. In this article we would analyse these CNN models along with a brief implementation of the same. The dataset used for this are highly regarded and have been the basis of several research papers.},
      keywords = {Neural Networks, Computer Vision, CNN, Image Processing},
      month = {January},
  }