Traffic Sign Detection and Recognition for Automated Driverless Cars Based on SSD

Self driving vehicles are cars or trucks in which human drivers are never required to take control to safely operate the vehicle. They can possibly reform urban portability by giving maintainable, protected, and advantageous, clog free transportability. The issues like reliably perceiving traffic lights, signs, indistinct path markings can be overwhelmed by utilizing the innovative improvement in the fields of Deep Learning DL . Here, Faster Region Based Convolution Neural Network F RCNN is proposed for detection and recognition of Traffic Lights TL and signs by utilizing transfer learning. The input can be taken from the dataset containing various images of traffic signals and signs as per Indian Traffic Signals. The model achieves its target by distinguishing the traffic light and signs with its right class type. The proposed framework can likewise be upgraded for safe driving in spite of hazy path markings. Aswathy Madhu | Veena S Nair "Traffic Sign Detection and Recognition for Automated Driverless Cars Based on SSD" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-5 , August 2020, URL: https://www.ijtsrd.com/papers/ijtsrd31888.pdf Paper Url :https://www.ijtsrd.com/computer-science/artificial-intelligence/31888/traffic-sign-detection-and-recognition-for-automated-driverless-cars-based-on-ssd/aswathy-madhu