The transport sector is commonly subordinate to several issues, such as traffic congestion
and accidents. Despite this, in recent years, it is also evolving with regard to cooperation …

Achieving the high accuracy of blind roads and crosswalks recognition is important for blind
guiding equipment to help blind people sense the surrounding environment. A lightweight …

With the continuous development of intelligent networks and autonomous driving
technologies, heterogeneous traffic flow represented by conventional vehicles (CV) …

We propose a practical Convolution Neural Network (CNN) model termed the CNN for
Semantic Segmentation for driver Assistance system (CSSA). It is a novel semantic …

This research presents the idea of a novel fully-Convolutional Neural Network (CNN)-based
model for probabilistic pixel-wise segmentation, titled Encoder-decoder-based CNN for …

Road dust is a mixture of fine and coarse particles released into the air due to an external
force, such as tire–ground friction or wind, which is harmful to human health when inhaled …

Driver and pedestrian safety can be aided by systems and methods to provide identification
and classification of objects in a vehicle travel path. Information about classified objects can …

The manual systems for road safety are inefficient, very time consuming and prone to error.
Automated systems face many challenges in detecting all road safety objects accurately and …

Forward neural network (FNN) execution relying on the algorithm of training and architecture
selection. Different parameters using for nip out the architecture of FNN such as the …

Collision warning is essential in Advanced Driver Assistance Systems. However, all the
studies focus on accurate assessment of risky situations without considering the driver's …