articleMachinesJun 23, 2023GOLD OA

YOLO-v1 to YOLO-v8, the Rise of YOLO and Its Complementary Nature toward Digital Manufacturing and Industrial Defect Detection

University of Huddersfield

Indexed incrossrefdoaj

Abstract

Since its inception in 2015, the YOLO (You Only Look Once) variant of object detectors has rapidly grown, with the latest release of YOLO-v8 in January 2023. YOLO variants are underpinned by the principle of real-time and high-classification performance, based on limited but efficient computational parameters. This principle has been found within the DNA of all YOLO variants with increasing intensity, as the variants evolve addressing the requirements of automated quality inspection within the industrial surface defect detection domain, such as the need for fast detection, high accuracy, and deployment onto constrained edge devices. This paper is the first to provide an in-depth review of the YOLO evolution…

Citation impact

1,073
total citations
FWCI
205.01
Percentile
100%
References
83
Citations per year

Authors

1

Topics & keywords

Keywords
  • Software deployment
  • Computer science
  • Object detection
  • Artificial intelligence
  • Pattern recognition (psychology)
  • Software engineering
UN Sustainable Development Goals
  • Industry, innovation and infrastructure
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