research-article

Residual Mask Based on MobileNet-V2 for Driver's Dangerous Behavior Recognition

Author:

Haotian WangAuthors Info & Claims

CSAI '19: Proceedings of the 2019 3rd International Conference on Computer Science and Artificial Intelligence

Pages 196 - 199

https://doi.org/10.1145/3374587.3374621

Published: 04 March 2020 Publication History

Abstract

We introduce a new residual mask into the inverted residual structure in MobileNet-V2, which significantly improved the performance of the original network, with only a minimal number of parameters added. We train our networks on a larger public dataset to detect distract behaviors of a driver. Experiments show that MobileNet-v2 with the proposed residual mask converges faster and achieves better accuracy than the original network.

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Digital Library

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Yan, S., Teng, Y., Smith, J. S., and Zhang, B. 2016. Driver behavior recognition based on deep convolutional neural networks. In 2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD) (pp. 636--641). IEEE.

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Cited By

Yasser FHatem SWaleed HAhmed ZHossam BAli RAtia A(2024)Enhancing Road Safety: A Comprehensive Driver Behavior Scoring Framework with K-Means Action Segmentation and Deep Learning Behavior Detection2024 Intelligent Methods, Systems, and Applications (IMSA)10.1109/IMSA61967.2024.10652666(616-621)Online publication date: 13-Jul-2024
https://doi.org/10.1109/IMSA61967.2024.10652666
Yasser FHatem SWaleed HAhmed ZHossam BAli RAtia A(2024)Driver Behavior Tracking: A Hierarchical Classification Approach2024 14th International Conference on Electrical Engineering (ICEENG)10.1109/ICEENG58856.2024.10566383(231-236)Online publication date: 21-May-2024
https://doi.org/10.1109/ICEENG58856.2024.10566383
Yasser FHatem SAhmed ZWaleed HHossam BAli RAtia A(2024)Driver and Vehicle Unsafe Behavior Tracking using Deep Learning2024 6th International Conference on Computing and Informatics (ICCI)10.1109/ICCI61671.2024.10485085(75-82)Online publication date: 6-Mar-2024
https://doi.org/10.1109/ICCI61671.2024.10485085
Show More Cited By

Index Terms

Residual Mask Based on MobileNet-V2 for Driver's Dangerous Behavior Recognition
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Object recognition

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CSAI '19: Proceedings of the 2019 3rd International Conference on Computer Science and Artificial Intelligence

December 2019

370 pages

ISBN:9781450376273

DOI:10.1145/3374587

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Shenzhen University: Shenzhen University

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 04 March 2020

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CSAI2019: 2019 3rd International Conference on Computer Science and Artificial Intelligence

December 6 - 8, 2019

IL, Normal, USA

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Cited By

Yasser FHatem SWaleed HAhmed ZHossam BAli RAtia A(2024)Enhancing Road Safety: A Comprehensive Driver Behavior Scoring Framework with K-Means Action Segmentation and Deep Learning Behavior Detection2024 Intelligent Methods, Systems, and Applications (IMSA)10.1109/IMSA61967.2024.10652666(616-621)Online publication date: 13-Jul-2024
https://doi.org/10.1109/IMSA61967.2024.10652666
Yasser FHatem SWaleed HAhmed ZHossam BAli RAtia A(2024)Driver Behavior Tracking: A Hierarchical Classification Approach2024 14th International Conference on Electrical Engineering (ICEENG)10.1109/ICEENG58856.2024.10566383(231-236)Online publication date: 21-May-2024
https://doi.org/10.1109/ICEENG58856.2024.10566383
Yasser FHatem SAhmed ZWaleed HHossam BAli RAtia A(2024)Driver and Vehicle Unsafe Behavior Tracking using Deep Learning2024 6th International Conference on Computing and Informatics (ICCI)10.1109/ICCI61671.2024.10485085(75-82)Online publication date: 6-Mar-2024
https://doi.org/10.1109/ICCI61671.2024.10485085
Xu JHuang ZLiu LLi XWei K(2023)Eye-Gaze Controlled Wheelchair Based on Deep LearningSensors10.3390/s2313623923:13(6239)Online publication date: 7-Jul-2023
https://doi.org/10.3390/s23136239
Liang YWang XYu ZGuo BZheng XSamtani S(2021)Energy-efficient Collaborative Sensing: Learning the Latent Correlations of Heterogeneous SensorsACM Transactions on Sensor Networks10.1145/344841617:3(1-28)Online publication date: 21-Jun-2021
https://dl.acm.org/doi/10.1145/3448416

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