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
Semantic segmentation was once thought to present a formidable prediction challenge in computer vision. Deep learning has made strides in recent years, making automated driving solutions a viable prospect. The majority of currently used semantic segmentation algorithms weren't created with automated vehicle operation in mind; instead, they were created for general-purpose image processing. We describe a dependable technique for semantic segmentation in autonomous cars in this article. A precise and current semantic segmentation system must be created right away for autonomous vehicles to operate in a safe and efficient manner. The foundation of the project is the idea of autonomous driving or self-driving cars. Without the ability to recognise and react to risks like pedestrians, other vehicles, traffic lanes, etc., autonomous vehicles cannot operate.
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Cite Article:
"Semantic segmentation self driving cars", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.8, Issue 4, page no.2771 - 2776, April-2023, Available :http://www.ijsdr.org/papers/IJSDR2304430.pdf
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Publication Details:
Published Paper ID: IJSDR2304430
Registration ID:205908
Published In: Volume 8 Issue 4, April-2023
DOI (Digital Object Identifier):
Page No: 2771 - 2776
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
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