Artificial Intelligence in Vehicular Wireless Networks: A Case Study Using ns-3-Reference-Cited by-同舟云学术

Artificial Intelligence in Vehicular Wireless Networks: A Case Study Using ns-3

Published:2022-06-22 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the WNS3 2022
language:
Short-container-title:

Author:

Drago Matteo¹,Zugno Tommaso²,Mason Federico¹,Giordani Marco¹,Boban Mate²,Zorzi Michele¹

Affiliation:

1. Department of Information Engineering, University of Padova, Italy

2. Huawei Technologies, Germany

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3532577.3532605

Reference32 articles.

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2. Abien Fred Agarap. 2018. Deep Learning using Rectified Linear Units (ReLu). arXiv preprint arXiv:1803.08375(2018). Abien Fred Agarap. 2018. Deep Learning using Rectified Linear Units (ReLu). arXiv preprint arXiv:1803.08375(2018).

3. Vehicle Trajectory Prediction and Collision Warning via Fusion of Multisensors and Wireless Vehicular Communications

4. Dynamic Programming

5. Mate Boban. 2014. GEMV2: Geometry Based Efficient Propagation Model for V2V Communication. http://vehicle2x.net/ Mate Boban. 2014. GEMV2: Geometry Based Efficient Propagation Model for V2V Communication. http://vehicle2x.net/

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