A multimodal deep fusion framework for highway traffic anomaly detection

Abstract This paper presents a novel framework for detecting and predicting abnormal traffic events on highways. Traditional traffic monitoring systems often rely on a single data source, which limits detection accuracy and robustness in complex environments. To address these challenges, we propose...

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Bibliographic Details

Main Authors:	Mengmeng Duan, Shaowei Sun, Mingzhou Liu
Format:	Artigo
Language:	Inglês
Published:	Nature Portfolio 2025-09-01
Series:	Scientific Reports
Subjects:	Multimodal deep fusion Heterogeneous graph neural network Traffic anomaly event Dynamic detection Static detection
Online Access:	https://doi.org/10.1038/s41598-025-18671-x
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