Using Bidirectional Encoder Representations from Transformers (BERT) to classify traffic crash severity types-Reference-Cited by-同舟云学术

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Using Bidirectional Encoder Representations from Transformers (BERT) to classify traffic crash severity types

Published:2023-06 Issue: Volume:3 Page:100007
ISSN:2949-7191
Container-title:Natural Language Processing Journal
language:en
Short-container-title:Natural Language Processing Journal

Author:

Oliaee Amir Hossein^ORCID,Das Subasish^ORCID,Liu Jinli^ORCID,Rahman M. Ashifur^ORCID

Publisher

Elsevier BV

Reference40 articles.

1. Finding and understanding pedal misapplication crashes using a deep learning natural language model;Bareiss;Traffic Inj. Prev.,2021

2. Narrative text analysis of Kentucky tractor fatality reports;Bunn;Accid. Anal. Prev.,2008

3. Evaluation of strategies to mitigate culvert-involved crashes;Chawla;Transp. Res. Rec. J. Transp. Res. Board,2021

4. Electra: Pre-training text encoders as discriminators rather than generators;Clark,2020

5. Transformer-XL: Attentive language models beyond a fixed-length context;Dai,2019

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