Action Recognition of Traffic Police by Attentive for Self-Driving Vehicles-Reference-Cited by-同舟云学术

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Action Recognition of Traffic Police by Attentive for Self-Driving Vehicles

Published:2022-10-20 Issue: Volume: Page:
ISSN:
Container-title:2022 International Conference on Advanced Technologies for Communications (ATC)
language:
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Author:

Ha Manh-Hung¹,Le Minh-Huy²,Dang Khoa Nguyen¹,Kim Dinh-Thai¹,Tran Van Luan³

Affiliation:

1. International School, Vietnam National University,Faculty of Applied Sciences,Hanoi,Vietnam,100000

2. PHENIKAA University,Faculty of Electrical and Electronic Engineering,Ha Dong,Hanoi,Vietnam,12116

3. School of Engineering, Eastern International University,Viet Nam

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9942959/9942960/09942963.pdf?arnumber=9942963

Reference16 articles.

1. Deep Neural Networks Using Residual Fast-Slow Refined Highway and Global Atomic Spatial Attention for Action Recognition and Detection

2. Unified Spatio-Temporal Attention Networks for Action Recognition in Videos

3. Action Recognition Improved by Correlations and Attention of Subjects and Scene

4. Non-Local Spatiotemporal Correlation Attention for Action Recognition

5. Computation-Affordable Recognition System for Activity Identification using a Smart Phone at Home

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