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A Decade of You Only Look Once (YOLO) for Object Detection

Main:29 Pages
30 Figures
Bibliography:10 Pages
16 Tables
Abstract

This review marks the tenth anniversary of You Only Look Once (YOLO), one of the most influential frameworks in real-time object detection. Over the past decade, YOLO has evolved from a streamlined detector into a diverse family of architectures characterized by efficient design, modular scalability, and cross-domain adaptability. The paper presents a technical overview of the main versions, highlights key architectural trends, and surveys the principal application areas in which YOLO has been adopted. It also addresses evaluation practices, ethical considerations, and potential future directions for the framework's continued development. The analysis aims to provide a comprehensive and critical perspective on YOLO's trajectory and ongoing transformation.

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@article{ramos2025_2504.18586,
  title={ A Decade of You Only Look Once (YOLO) for Object Detection },
  author={ Leo Thomas Ramos and Angel D. Sappa },
  journal={arXiv preprint arXiv:2504.18586},
  year={ 2025 }
}
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