In recent years, deep learning has evolved as a rapidly growing and stimulating field of
machine learning and has redefined state-of-the-art performances in a variety of …

In the development of smart cities, the intelligent transportation system (ITS) plays a major
role. The dynamic and chaotic nature of the traffic information makes the accurate …

Spatio-temporal forecasting is an open research field whose interest is growing
exponentially. In this work we focus on creating a complex deep neural framework for spatio …

Traffic forecasting is an important prerequisite for the application of intelligent transportation
systems in urban traffic networks. The existing works adopted RNN and CNN/GCN, among …

Mental fatigue is a state that may occur due to excessive work or long-term stress.
Electroencephalography (EEG) is considered a reliable standard for mental fatigue …

Transportation data in a smart city environment is increasingly becoming available. This
data availability allows building smart solutions that are viewed as meaningful by both city …

Increasing traffic congestion is a major obstacle to the development of cities. The prediction
of traffic flow is very important to city planning and dredging. A good model of flow is able to …

Emotion detection using electroencephalogram (EEG) signals has gained widespread
acceptance in consumer preference study. It has been observed that emotion classification …

In a fast-moving world, transportation consumes most of the time and resources. Traffic
prediction has become a thrust application for machine learning algorithms to overcome the …

In modern cities video surveillance becomes an important part for protection and security. In
modern cities for security and protection smart cameras equipped with intelligent analysis of …