A semantic understanding of road traffic can help people understand road traffic flow
situations and emergencies more accurately and provide a more accurate basis for anomaly …

Diverse and wide-range applications of integrated circuits (ICs) and the development of
Cyber Physical System (CPS), more and more third-party manufacturers are involved in the …

Artificial Intelligence (AI) technology is extensively applied in all walks of life with continuous
acceleration of the construction of smart cities. The current research status of intelligent …

Short‐term load forecasting (STLF) plays a very important role in improving the economy
and stability of the power system operation. With the smart meters and smart sensors widely …

Accurate and real-time traffic flow prediction plays a central role for efficient traffic
management. Software Defined Networking (SDN) is one of the key concerns in networking …

In this paper, Deep Neural Networks (DNN) with Bat Algorithms (BA) offer a dynamic form of
traffic control in Vehicular Adhoc Networks (VANETs). The former is used to route vehicles …

In order to generate a probability density function (PDF) for fitting the probability distributions
of practical data, this study proposes a deep learning method which consists of two …

Traffic management systems capture tremendous video data and leverage advances in
video processing to detect and monitor traffic incidents. The collected data are traditionally …

Automatic image annotation is a key step in image retrieval and image understanding. In this
paper, we present an end-to-end automatic image annotation method based on a deep …

Automatic traffic flow classification is useful to reveal road congestions and accidents.
Nowadays, roads and highways are equipped with a huge amount of surveillance cameras …