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  Published Paper Details:

  Paper Title

Ambulance Detection Using YOLOv8

  Authors

  Aakansha Kumar,  Dr. Manisha Bharti

  Keywords

Emergency vehicles, YOLOv8, object detection, deep learning, image segmentation

  Abstract


The escalating urban population in India has given rise to a surge in traffic congestion within cities, posing challenges for ambulances to navigate through densely populated streets. This issue is exacerbated by a general lack of public awareness regarding the critical importance of yielding to emergency vehicles. To address this problem, our research focuses on training the YOLOv8 model for effective ambulance identification amidst other vehicles on the road. YOLO, distinguished for its efficacy in object detection, notably excels in swift processing speeds and exceptional accuracy. This project emphasizes the utilization of YOLOv8, which demonstrates an 84.62% precision, a 75.93% recall, and an F1-score of 79.98% for ambulance detection and the application of deep learning methodologies for image segmentation, aiming to enhance emergency vehicle navigation in congested urban environments.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT24A4568

  Paper ID - 258307

  Page Number(s) - n556-n563

  Pubished in - Volume 12 | Issue 4 | April 2024

  DOI (Digital Object Identifier) -    http://doi.one/10.1729/Journal.39145

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Aakansha Kumar,  Dr. Manisha Bharti,   "Ambulance Detection Using YOLOv8", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.12, Issue 4, pp.n556-n563, April 2024, Available at :http://www.ijcrt.org/papers/IJCRT24A4568.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


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ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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