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Predicting Vehicle Pose in Six Degrees of Freedom from Single Image in Real-World Traffic Environments Using Deep Pretrained Convolutional Networks and Modified Centernet Cover

Predicting Vehicle Pose in Six Degrees of Freedom from Single Image in Real-World Traffic Environments Using Deep Pretrained Convolutional Networks and Modified Centernet

Open Access
|Aug 2024

Authors

Suresh Kolekar

Computer Engineering Department, Symbiosis Institute of Technology, Symbiosis International (Deemed) University, Pune, India
Symbiosis Centre of Applied A.I. (SCAAI), Symbiosis International (Deemed) University, Pune, India

Shilpa Gite

shilpa.gite@sitpune.edu.in

Symbiosis Centre of Applied A.I. (SCAAI), Symbiosis International (Deemed) University, Pune, India
Artificial Intelligence and Machine Learning Department, Symbiosis Institute of Technology, Symbiosis International (Deemed) University, Pune, India

Biswajeet Pradhan

Biswajeet.Pradhan@uts.edu.au

Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), School of Civil and Environmental Engineering, Faculty of Engineering and I.T., University of Technology Sydney, Ultimo, Australia

Abdulla Alamri

Department of Geology and Geophysics, College of Science, King Saud University, Riyadh, Saudi Arabia
Language: English
Submitted on: Apr 18, 2024
Published on: Aug 6, 2024
Published by: Professor Subhas Chandra Mukhopadhyay
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2024 Suresh Kolekar, Shilpa Gite, Biswajeet Pradhan, Abdulla Alamri, published by Professor Subhas Chandra Mukhopadhyay
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.