首页|University of Malaysia Sabah Researchers Add New Data to Research in Machine Lea rning (A Survey on Vehicular Traffic Flow Anomaly Detection Using Machine Learni ng)
University of Malaysia Sabah Researchers Add New Data to Research in Machine Lea rning (A Survey on Vehicular Traffic Flow Anomaly Detection Using Machine Learni ng)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-A new study on artificial intelligence is now available. According to news reporting from the University of Malaysia S abah by NewsRx journalists, research stated, "Vehicular traffic flow anomaly det ection is crucial for traffic management, public safety, and transportation effi ciency." The news journalists obtained a quote from the research from University of Malay sia Sabah: "It assists experts in responding promptly to abnormal traffic condit ions and making decisions to improve the traffic flow. This survey paper offers an overview of the application of machine learning to detect anomalies in the tr affic flow. Through an extensive review of the literature from the Scopus databa se, this paper explores the technical aspects of traffic flow anomaly detection using machine learning, including data sources, data processing approaches, mach ine learning algorithms, and evaluation metrics." According to the news reporters, the research concluded: "Additionally, the pape r highlights the emerging research opportunities for researchers in enhancing tr affic flow anomaly detection using machine learning."
University of Malaysia SabahCyborgsE merging TechnologiesMachine Learning
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