An Evaluation of Advancements in YOLO Algorithm

Volume 18, Issue 1,  2024

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Author(s):

Nasreen Jawaid Institute of Mathematics and Computer Science, University of Sindh Jamshoro, Pakistan, nasreenjawaid07@gmail.com

Najma Imtiaz Ali Institute of Mathematics and Computer Science, University of Sindh Jamshoro, Pakistan, najma.channa@usindh.edu.pk

Kamran Taj Pathan Department of Information Technology, Government College University Hyderabad, Pakistan, kamran.taj@gcuh.edu.pk

Imtiaz Ali Brohi Department of Information Technology, Government College University Hyderabad, Pakistan, imtiaz.brohi@gcuh.edu.pk

Abstract The development and refinement of object detection models have significantly advanced computer vision, with the YOLO (You Only Look Once) framework emerging as a leading method due to its efficiency and real-time processing capabilities. This paper provides a detailed review of YOLO's evolution, from its inception to its most recent iterations. Key improvements in accuracy, speed, and model architecture across different YOLO versions are discussed. The paper also explores YOLO's diverse applications, including autonomous vehicles, surveillance systems, and healthcare, showcasing its adaptability and broad impact. Despite its success, YOLO faces challenges, particularly in balancing speed and accuracy. This review highlights these challenges and identifies potential areas for future research aimed at further optimizing YOLO models.
Keywords Data analysis; Object detection; YOLO; review
Year 2024
Volume 18
Issue 1
Type Research paper, manuscript, article
Journal Name Journal of Information & Communication Technology
Publisher Name ILMA University
Jel Classification -
DOI -
ISSN no (E, Electronic) 2075-7239
ISSN no (P, Print) 2415-0169
Country Pakistan
City Karachi
Institution Type University
Journal Type Open Access
Manuscript Processing Blind Peer Reviewed
Format PDF
Paper Link https://jict.ilmauniversity.edu.pk/journal/jict/18.1/6.pdf
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