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IJSDR
INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15

Issue: April 2024

Volume 9 | Issue 4

Impact factor: 8.15

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Paper Title: A Study on Current Trends in Deep Learning for Autonomous Driving
Authors Name: Sivapriya Rajan , Dr.Rahul Shajan
Unique Id: IJSDR2303230
Published In: Volume 8 Issue 3, March-2023
Abstract: Abstract: Recent developments in autonomous driving technology have been largely driven by deep learning. Deep neural networks are now the preferred approach for tackling challenging problems in autonomous driving, such as vision, control, and decision-making, thanks to the quick rise in processing power and the accessibility of vast amounts of data. The creation of end-to-end deep learning frameworks, which allow the optimization of the complete system in a single training procedure, is one of the very latest trends in deep learning for autonomous driving. The systems' accuracy and robustness have increased as a result. The adoption of reinforcement learning methods, which enable autonomous cars to learn from their own mistakes and improve their decision-making over time, is another development. The use of generative adversarial networks (GANs) for various autonomous driving tasks, such as picture synthesis and domain adaption, has also seen a substantial growth in research. Powerful generative models known as GANs can be trained to produce new data that closely matches existing data. In general, deep learning continues to be essential to the creation of autonomous vehicle systems. It is anticipated that deep learning will continue to drive innovation in this field and result in more advanced and secure autonomous driving systems in the future as more data becomes available and computing power increases. (Abstract)
Keywords: Index Terms: Deep learning, GAN, reinforcement, perception.
Cite Article: "A Study on Current Trends in Deep Learning for Autonomous Driving", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.8, Issue 3, page no.1370 - 1373, March-2023, Available :http://www.ijsdr.org/papers/IJSDR2303230.pdf
Downloads: 000337353
Publication Details: Published Paper ID: IJSDR2303230
Registration ID:204958
Published In: Volume 8 Issue 3, March-2023
DOI (Digital Object Identifier):
Page No: 1370 - 1373
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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