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[HTML][HTML] Spoken instruction understanding in air traffic control: Challenge, technique, and application
Y Lin - Aerospace, 2021 - mdpi.com
In air traffic control (ATC), speech communication with radio transmission is the primary way
to exchange information between the controller and aircrew. A wealth of contextual …
to exchange information between the controller and aircrew. A wealth of contextual …
[HTML][HTML] A systematic review of traffic incident detection algorithms
Traffic incidents have negative impacts on traffic flow and the gross domestic product of most
countries. In addition, they may result in fatalities and injuries. Thus, efficient incident …
countries. In addition, they may result in fatalities and injuries. Thus, efficient incident …
TFGAN: Traffic forecasting using generative adversarial network with multi-graph convolutional network
Traffic forecasting constitutes a task of great importance in intelligent transport systems.
Owing to the non-Euclidean structure of traffic data, the complicated spatial correlations, and …
Owing to the non-Euclidean structure of traffic data, the complicated spatial correlations, and …
Bayesian dynamic extreme value modeling for conflict-based real-time safety analysis
C Fu, T Sayed - Analytic methods in accident research, 2022 - Elsevier
Real-time safety analysis and optimization using surrogate safety measures such as traffic
conflicts and techniques such extreme value theory (EVT) models is an emerging research …
conflicts and techniques such extreme value theory (EVT) models is an emerging research …
[HTML][HTML] Alternative prioritization of freeway incident management using autonomous vehicles in mixed traffic using a type-2 neutrosophic number based decision …
Traffic incident management is combining the assets of authorities to identify, deal with, and
manage traffic problems as rapidly as possible while providing the safety of on-scene …
manage traffic problems as rapidly as possible while providing the safety of on-scene …
Traffic congestion detection from surveillance videos using deep learning
GB Madhavi, AD Bhavani, YS Reddy… - … Engineering & their …, 2023 - ieeexplore.ieee.org
Countless cameras, both public and private, have been installed in recent years for the
objectives of surveillance, the monitoring of anomalous human activities, and traffic …
objectives of surveillance, the monitoring of anomalous human activities, and traffic …
[PDF][PDF] Anomaly detection in time series using deep learning
Time series anomaly detection has ever existed as a fundamental analysis approach. The
early time series anomaly detection techniques are mainly statistical and machine learning …
early time series anomaly detection techniques are mainly statistical and machine learning …
Improving traffic accident severity prediction using MobileNet transfer learning model and SHAP XAI technique
OI Aboulola - PLoS one, 2024 - journals.plos.org
Traffic accidents remain a leading cause of fatalities, injuries, and significant disruptions on
highways. Comprehending the contributing factors to these occurrences is paramount in …
highways. Comprehending the contributing factors to these occurrences is paramount in …
A novel deep learning approach for anomaly detection of time series data
Z Ji, J Gong, J Feng - Scientific Programming, 2021 - Wiley Online Library
Anomalies in time series, also called “discord,” are the abnormal subsequences. The
occurrence of anomalies in time series may indicate that some faults or disease will occur …
occurrence of anomalies in time series may indicate that some faults or disease will occur …
Blockchain-enabled internet of vehicles applications
J Gao, C Peng, T Yoshinaga, G Han, S Guleng, C Wu - Electronics, 2023 - mdpi.com
Internet of Vehicles (IoV) is a network that connects vehicles and everything. IoV shares
traffic data by connecting vehicles with the surrounding environment, which brings huge …
traffic data by connecting vehicles with the surrounding environment, which brings huge …