In the recent times, there has been a lot of speculation related to advanced driver‐
assistance system (ADAS) which provides best driving experience for the drivers. ADAS …

Annually, deep learning algorithms have proven their effectiveness in many vision-based
applications, such as autonomous driving, traffic, and congestion monitoring, and so on. In …

Growing vehicular traffic in urban areas creates a mess for authorities to handle city traffic.
With the lack of human resources, authorities are moving towards the use of smart and auto …

Recognizing and classifying traffic signs is a challenging task that can significantly improve
road safety. Deep neural networks have achieved impressive results in various applications …

In this paper we propose a novel and efficient hardware implementation of an image
watermarking system based on the Haar Discrete Wavelet Transform (DWT). DWT is used in …

Traffic sign detection (TSD) using convolutional neural networks (CNN) is promising and
intriguing for autonomous driving. Especially, with sophisticated large-scale CNN models …

Automatic traffic sign recognition enhances driver interactivity while driving. It improves the
vigilance of the driver by alarming-him/her of signs that he/she may not perceive. In this …

The vision problem of drivers during the night is mainly owing to the high-intensity headlight-
beam of the oncoming vehicle from the reverse direction. It causes temporary blindness to …

In this paper, two main contributions are presented to manage the power flow between a
wind turbine and a solar power system. The first one is to use the fuzzy logic controller as an …

This paper presents a design methodology of a real-time embedded system that processes
the detection and recognition of road signs while the vehicle is moving. An efficient algorithm …