A Deep Convolutional Neural Network for Traffic Sign Classification and Detection with Voice Recognition - K.Prakash (Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2021)
Traffic Sign Detection and Classification play an important major role nowadays in our daily life. Anyway, Traffic Signs are present on roads. Even though, often the drivers do mistakes. It’s very hard to recognize and detect traffic signs while travelling on roads. Drivers may misinterpret traffic signs, this leads to Accidents and results in damage to the vehicle. To overcome this problem this project introduces a concept named Traffic Sign Detection and Classification with Voice Recognition. This model is built by using CNN to extract the images and classify the traffic signs. Here DCCNN model is built to improve overall accuracy and speed. Here Classification process is also tested with AlexNet, VGG16, VGG19. This system reveals output that recognizes the traffic signs automatically that helps to detect the street condition and alerts driver soon and this enables to build a smart vehicle.