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A deep learning approach for detecting traffic accidents from social media data · Study

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ArticleA deep learning approach for detecting traffic accidents from social media data

Zhenhua Zhang2017

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Articlegreen2017

A deep learning approach for detecting traffic accidents from social media data

Zhenhua Zhang · Qing He · Jing Gao · Ming Ni

356 citations·0/0 files stored·Transportation Research Part C Emerging Technologies

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Traffic Prediction and Management Techniques Traffic and Road Safety Text and Document Classification Technologies

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References

2010The Political Power of Social Media 2017Deep learning for short-term traffic flow prediction 1995Historical Development of the Newton–Raphson Method 2012TEDAS: A Twitter-based Event Detection and Analysis System 2016From Twitter to detector: Real-time traffic incident detection using social media data 2014Urban activity pattern classification using topic models from online geo-location data 2016Exploring the capacity of social media data for modelling travel behaviour: Opportunities and challenges 2016Forecasting the Subway Passenger Flow Under Event Occurrences With Social Media

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2018The station-free sharing bike demand forecasting with a deep learning approach and large-scale datasets 2020How to Build a Graph-Based Deep Learning Architecture in Traffic Domain: A Survey

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Details

Year2017

Typearticle

Published2017-12-22

VenueTransportation Research Part C Emerging Technologies

ISSN-L0968-090X

Languageen

Citations356

Files0 public / 0

ShelfTraffic Prediction and Management Techniques

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doi10.1016/j.trc.2017.11.027

openalex_workW2963048283

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