Traffic closed-circuit television (CCTV) devices can be used to detect and track objects on roads by designing applying artificial intelligence deep learning models. However, extracting useful information from the detected determining occurrence of traffic accidents are usually difficult. This paper proposes a CCTV frame-based hybrid accident classification model that enables identification whe...

Internet traffic classification plays important roles in numerous areas such as network management, traffic engineering, QoS provisioning etc. Prior traffic analysis is an essential requirement for existing classification schemes to classify unknown traffic. To overcome the drawback of the previous classification scheme to meet the requirements of the network activities, we propose online self-...

Accurate classification of traffic flows is an essential step for administrators to detect intrusion or malicious attacks, forbidden applications, or simply new applications which may impact the future provisioning of network resources. In this work four major topics are considered in connection with traffic classification activities. First, a novel validation method is proposed for characteriz...

Traffic classification is an automated process which categorizes computer network traffic according to various parameters into a number of traffic classes. Many supervised classification algorithms and unsupervised clustering algorithms have been applied to categorize Internet traffic. Traditional traffic classification methods include the port-based prediction methods and payloadbased deep ins...

Traffic image classification to identify the traffic density will support the traffic problems such as intelligent traffic signal control, traffic planning, etc. This paper proposes a novel traffic image classification method based on horizontal slice algorithm and histogram. The system model is designed and evaluated with the image datasets of Ho Chi Minh city, Vietnam. The best accuracy resul...