# A Comprehensive Review of YOLO: From YOLOv1 and Beyond

**Authors:** Juan Terven, Diana Cordova-Esparza  
**arXiv:** [2304.00501](https://arxiv.org/abs/2304.00501)  
**Date:** 2023-04-02  
**Summary page:** https://www.summarizepaper.com/fr/paper/2304.00501v3/

## 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 to YOLOv8 and YOLO-NAS. 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.