Efficient traffic signal detection with tiny YOLOv4: enhancing road safety through computer vision

Abstract

As  decades  go by, technology  advances  and  everything  around us  becomes smarter,  such  as  televisions,  mobile  phones,  robots,  and  so  on.  Artificial intelligence (AI) is  applied  in  these  technologies  where  AI  assists  the computer   in   making   judgments   like   humans,   and   this   intelligence   is artificially  fed  to  the  model.  The  self-driving  technique  is  a  developing technology.  Autonomous  driving  has  been  a  broad  and  fast-expanding technology over the last decade. This model is carried out using the tiny you only   look  once (YOLO)   algorithm.   YOLO  is  mainly  used   for  object detection classification. Tiny YOLO model is explored for the traffic signal detection.  ROBI  FLOW  dataset  is  used  for  object  detection  which  contains 2000+ image data to train the tiny YOLO model for traffic signal detection in  real  time.  This  model  gives  an  improved  accuracy  and  lightweight implementation compared to other models. Tiny YOLO is fast and accurate model for real-time traffic signal detection.