Correction to “Improving Multi-Agent Trajectory Prediction Using Traffic States on Interactive Driving Scenarios” [May 23 2708-2715]-Reference-Cited by-同舟云学术

Correction to “Improving Multi-Agent Trajectory Prediction Using Traffic States on Interactive Driving Scenarios” [May 23 2708-2715]

Published:2023-11 Issue:11 Volume:8 Page:7519-7519
ISSN:2377-3766
Container-title:IEEE Robotics and Automation Letters
language:
Short-container-title:IEEE Robot. Autom. Lett.

Author:

Vishnu Chalavadi¹^ORCID,Abhinav Gottala Vineel¹^ORCID,Roy Debaditya²^ORCID,Mohan C. Krishna¹,Babu Ch. Sobhan¹^ORCID

Affiliation:

1. Department of Computer Science and Engineering, Indian Institute of Technology Hyderabad, Telangana, India

2. Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR), Singapore

Funder

Design and Development of Machine Learning Algorithms for Traffic Analytics

National Research Foundation Singapore through its AI Singapore Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Control and Optimization,Computer Science Applications,Computer Vision and Pattern Recognition,Mechanical Engineering,Human-Computer Interaction,Biomedical Engineering,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/7083369/10254630/10273669.pdf?arnumber=10273669

Reference1 articles.

1. Improving Multi-Agent Trajectory Prediction Using Traffic States on Interactive Driving Scenarios

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