Deep Learning and Autonomous Vehicles: Strategic Themes, Applications, and Research Agenda Using SciMAT and Content-Centric Analysis, a Systematic Review
- DOI
- 10.3390/make5030041
- Published
- 07
- Container
- Machine Learning and Knowledge Extraction
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.3390/make5030041,
title = {Deep Learning and Autonomous Vehicles: Strategic Themes, Applications, and Research Agenda Using SciMAT and Content-Centric Analysis, a Systematic Review},
author = {Fábio Eid Morooka and Adalberto Manoel Junior and Tiago F. A. C. Sigahi and Jefferson de Souza Pinto and Izabela Simon Rampasso and Rosley Anholon},
year = {2023},
journal = {Machine Learning and Knowledge Extraction},
doi = {10.3390/make5030041},
url = {https://doi.org/10.3390/make5030041}
}RIS
TY - JOUR TI - Deep Learning and Autonomous Vehicles: Strategic Themes, Applications, and Research Agenda Using SciMAT and Content-Centric Analysis, a Systematic Review AU - Fábio Eid Morooka AU - Adalberto Manoel Junior AU - Tiago F. A. C. Sigahi AU - Jefferson de Souza Pinto AU - Izabela Simon Rampasso AU - Rosley Anholon PY - 2023 JO - Machine Learning and Knowledge Extraction DO - 10.3390/make5030041 UR - https://doi.org/10.3390/make5030041 ER -
APA
Morooka, F. E., Junior, A. M., Sigahi, T. F. A. C., Pinto, J. D. S., Rampasso, I. S., & Anholon, R. (2023). Deep Learning and Autonomous Vehicles: Strategic Themes, Applications, and Research Agenda Using SciMAT and Content-Centric Analysis, a Systematic Review. Machine Learning and Knowledge Extraction. https://doi.org/10.3390/make5030041
Source records
- doaj · retrieved 2026-09-25T03:41:05.998Z