reviewMachine Learning and Knowledge ExtractionNov 20, 2023GOLD OA

A Comprehensive Review of YOLO Architectures in Computer Vision: From YOLOv1 to YOLOv8 and YOLO-NAS

Instituto Politécnico Nacional · Autonomous University of Queretaro

Indexed incrossrefdoaj

Abstract

YOLO has become a central real-time object detection system for robotics, driverless cars, and video monitoring applications. We present a comprehensive analysis of YOLO’s evolution, examining the innovations and contributions in each iteration from the original YOLO up to YOLOv8, YOLO-NAS, and YOLO with transformers. We start by describing the standard metrics and postprocessing; then, we discuss the major changes in network architecture and training tricks for each model. Finally, we summarize the essential lessons from YOLO’s development and provide a perspective on its future, highlighting potential research directions to enhance real-time object detection systems.

Citation impact

2,489
total citations
FWCI
282.70
Percentile
100%
References
107
Citations per year

Authors

3

Topics & keywords

Keywords
  • Computer science
  • Architecture
  • Artificial intelligence
  • Object detection
  • Robotics
  • Systems engineering
  • Human–computer interaction
  • Engineering
UN Sustainable Development Goals
  • Industry, innovation and infrastructure
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Funding