YOLOv1 to YOLOv10: The Fastest and Most Accurate Real-time Object Detection Systems

This is a comprehensive review of the YOLO series of systems. Different from previous literature surveys, this review article reexamines the characteristics of the YOLO series from the latest technical point of view. At the same time, we also analyzed how the YOLO series continued to influence and promote realtime computer vision-related research and led to the subsequent development of computer vision and language models. We take a closer look at how the methods proposed by the YOLO series in the past ten years have affected the development of subsequent technologies and show the applications of YOLO in various fields. We hope this article can play a good guiding role in subsequent real-time computer vision development.

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Publication Details

Journal
APSIPA Transactions on Signal and Information Processing
Published
2024-11-13
DOI
https://doi.org/10.1561/116.20240058
Citations
126
Primary Topic
COVID-19 diagnosis using AI
Type
article
Field-Weighted Citation Impact
50.94
Controls
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article

YOLOv1 to YOLOv10: The Fastest and Most Accurate Real-time Object Detection Systems

Chien-Yao Wang, Hong-Yuan Mark Liao
126 citations
APSIPA Transactions on Signal and Information Processing
COVID-19 diagnosis using AI
50.94
article

YOLOv1 to YOLOv10: The Fastest and Most Accurate Real-time Object Detection Systems

Chien-Yao Wang, Hong-Yuan Mark Liao
article en
126 citations

Abstract

This is a comprehensive review of the YOLO series of systems. Different from previous literature surveys, this review article reexamines the characteristics of the YOLO series from the latest technical point of view. At the same time, we also analyzed how the YOLO series continued to influence and promote realtime computer vision-related research and led to the subsequent development of computer vision and language models. We take a closer look at how the methods proposed by the YOLO series in the past ten years have affected the development of subsequent technologies and show the applications of YOLO in various fields. We hope this article can play a good guiding role in subsequent real-time computer vision development.

APSIPA Transactions on Signal and Information ProcessingVol. 13(1)
National Taipei University of Technology (TW), National Chung Hsing University (TW), Institute of Political Science, Academia Sinica (TW), Institute of Information Science, Academia Sinica (TW)
Openalex Percentile: Top 0%
COVID-19 diagnosis using AI
50.94
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