- Published
- 2023-11-20
- Venue
- Machine Learning and Knowledge Extraction, vol. 5, no. 4, pp. 1680-1716
- Cited by
- 3,088
- Open access
- Yes, gold
- DOI
- 10.3390/make5040083
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.
Cite this paper
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- APA 7
Terven, J. R., Esparza, D. M. C., & Romero-González, J.-A. (2023). A Comprehensive Review of YOLO Architectures in Computer Vision: From YOLOv1 to YOLOv8 and YOLO-NAS. Machine Learning and Knowledge Extraction, 5(4), 1680–1716. https://doi.org/10.3390/make5040083
- MLA 9
Terven, Juan R., et al. "A Comprehensive Review of YOLO Architectures in Computer Vision: From YOLOv1 to YOLOv8 and YOLO-NAS." Machine Learning and Knowledge Extraction, vol. 5, no. 4, 2023, pp. 1680–1716, https://doi.org/10.3390/make5040083.
- Chicago
Terven, Juan R., Diana Margarita Córdova Esparza, and Julio-Alejandro Romero-González. "A Comprehensive Review of YOLO Architectures in Computer Vision: From YOLOv1 to YOLOv8 and YOLO-NAS." Machine Learning and Knowledge Extraction 5, no. 4 (2023): 1680–1716. https://doi.org/10.3390/make5040083.
- GOST
Terven J. R., Esparza D. M. C., Romero-González J.-A. A Comprehensive Review of YOLO Architectures in Computer Vision: From YOLOv1 to YOLOv8 and YOLO-NAS // Machine Learning and Knowledge Extraction. — 2023. — Vol. 5, № 4. — P. 1680–1716. — URL: https://doi.org/10.3390/make5040083
- BibTeX
@article{terven2023comprehensive, title = {{A Comprehensive Review of YOLO Architectures in Computer Vision: From YOLOv1 to YOLOv8 and YOLO-NAS}}, author = {Juan R. Terven and Diana Margarita Córdova Esparza and Julio-Alejandro Romero-González}, journal = {Machine Learning and Knowledge Extraction}, year = {2023}, volume = {5}, number = {4}, pages = {1680--1716}, doi = {10.3390/make5040083}, url = {https://doi.org/10.3390/make5040083} }- RIS
TY - JOUR AU - Terven, Juan R. AU - Esparza, Diana Margarita Córdova AU - Romero-González, Julio-Alejandro TI - A Comprehensive Review of YOLO Architectures in Computer Vision: From YOLOv1 to YOLOv8 and YOLO-NAS JO - Machine Learning and Knowledge Extraction VL - 5 IS - 4 SP - 1680 EP - 1716 PY - 2023 DA - 2023/11/20 DO - 10.3390/make5040083 UR - https://doi.org/10.3390/make5040083 ER -
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