Abstract

Autonomous driving technology has made significant advances in recent years. In order to make self-driving cars more practical, they are required to operate safely and reliably even under adverse driving condition. The object detection based on deep learning is an important application in deep learning technology, which is characterized by its strong capability of features learning and feature representation compared with the traditional object detection method. After analyzing the characteristics of videos shot by the camera, we choose to use deep learning to train a vehicle detection model to detect targets in video. In the end, we use trained data set to control the speed and navigate the vehicle in crises situations. Conversely, not much research is going on of usage such networks for elaborating of real time data. The goal of this work is exploring, experimenting and providing new approaches of classification non-stationery data using neural network. Murugan Venkatesan | S. Gokul | Dr. R. Indra Gandhi"Artificial Neural Network Based Automated Escalating Tools for Crises Navigation" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-3 , April 2018, URL: http://www.ijtsrd.com/papers/ijtsrd10900.pdf http://www.ijtsrd.com/engineering/computer-engineering/10900/artificial-neural-network-based-automated-escalating-tools-for-crises-navigation/murugan-venkatesan

Authors and Affiliations