Mobile IoT-RoadBot-Reference-Cited by-同舟云学术

Mobile IoT-RoadBot

Published:2022-10-14 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 28th Annual International Conference on Mobile Computing And Networking
language:
Short-container-title:

Author:

Forkan Abdur Rahim Mohammad¹,Kang Yong-Bin¹,Marti Felip¹,Joachim Shane¹,Banerjee Abhik¹,Milovac Josip Karabotic¹,Jayaraman Prem Prakash¹,McCarthy Chris¹,Ghaderi Hadi¹,Georgakopoulos Dimitrios¹

Affiliation:

1. Swinburne University of Technology, Melbourne, Australia

Funder

Australian Government 5G Innovation Initiative

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3495243.3558271

Reference5 articles.

1. Maged Gouda , Bruno Arantes de Achilles Mello, and Karim El-Basyouny . 2021 . Automated object detection, mapping, and assessment of roadside clear zones using LiDAR data. Transportation research record 2675, 12 (2021), 432--448. Maged Gouda, Bruno Arantes de Achilles Mello, and Karim El-Basyouny. 2021. Automated object detection, mapping, and assessment of roadside clear zones using LiDAR data. Transportation research record 2675, 12 (2021), 432--448.

2. The Mapillary Vistas Dataset for Semantic Understanding of Street Scenes

3. A Novel Road Maintenance Prioritisation System Based on Computer Vision and Crowdsourced Reporting

4. Multimodal Classification of Urban Micro-Events

5. M. Sukel , S. Rudinac , and M. Worring . 2020 . Urban Object Detection Kit: A System for Collection and Analysis of Street-Level Imagery. In 2020 International Conference on Multimedia Retrieval. 509--516 . M. Sukel, S. Rudinac, and M. Worring. 2020. Urban Object Detection Kit: A System for Collection and Analysis of Street-Level Imagery. In 2020 International Conference on Multimedia Retrieval. 509--516.

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