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

“A Comprehensive Review of YOLO Architectures in Computer Vision: From YOLOv1 to YOLOv8 and YOLO-NAS” (2023), by Juan R. Terven et al. Computer Science research paper. Original abstract below, unchanged. A free PDF is available.

- Authors: Juan R. Terven, Diana Margarita Córdova Esparza, Julio-Alejandro Romero-González
- Published: November 20, 2023
- Field: Computer Science
- DOI: https://doi.org/10.3390/make5040083
- Free PDF: https://arxiv.org/pdf/2304.00501

## 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.

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