In this work, the YOLOv5 algorithm is employed, in order to find a solution for the efficient and fast detection of traffic cones. The YOLOv5 can achieve a high detection accuracy with the score of IoU up to 91.31%. The proposed method is been applied to an RGB roadwork image dataset,...
摘要: We have developed a real-time traffic incident detection system for the Tokyo Metropolitan Expressway. This system monitors current traffic using probe-car data and compares actual traffic in real time with the usual traffic, which is estimated in advance using batch processing....
Current trends are use of machine learning (ML) techniques for IP traffic classification. In this research paper, a real time internet traffic dataset has been developed using packet capturing tool for 2 second packet capturing duration and other datasets have been developed by reducing number of ...
Results demonstrated an improvement in average accuracy and a reduction in execution time. In an experiment conducted by Zhu et al.15 the performance of the latest version of YOLOv5 was evaluated based on a traffic sign recognition dataset they created. Through a comprehensive comparison with SSD,...
Accurate and real-time trajectory data publishing plays an important role in providing users with the latest traffic and road condition information to help in rationally planning travel time and routes. However, the improper publishing of location inform
Tüm işlemler başarılı olur ise web socket bağlantısını bekleyecek. web socket bağlantısını başlatmak için index.html dosyasını herhangi bir tarayıcıda başlatılması. Referanslar Dataset...
GoAccess is a real-time web log analyzer and interactive viewer that runs in a terminal in *nix systems or through your browser. - allinurl/goaccess
The microprocessor sends a signal to the Gizduino to process the time of the red light's on state. The microcontroller was programmed with the traffic signals. When it receives a signal from the microprocessor, it added an extra seconds to the red light's on state. Afterwards, when it ...
Using the systems and techniques described above, various experiments were conducted, the results of which are now described. The experimental setup included a traffic dataset, baseline approaches, and fitness measurements. Other implementations are also possible. ...
Bayesian Regularization helps in achieving better generalization of the dataset, thereby enabling the detection of botnet activity even of those bots which were never used in training the Neural Network. Hence such a framework is suitable for detection of newer and unseen botnets in live traffic of...