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

> 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...

## Metadata
- Authors: Juan Terven, Diana‐Margarita Córdova‐Esparza, Julio-Alejandro Romero-González
- Journal: Machine Learning and Knowledge Extraction
- Published: 2023-11-20
- DOI: https://doi.org/10.3390/make5040083
- Citations: 2,645
- Source: OpenAlex
- Access: Open Access

## Technology Hub
- Hub: Computer Vision
- Discipline: Computer Science / AI
- Hub URL: https://science-database.com/technology/computer-vision
- Hub llms.txt: https://science-database.com/technology/computer-vision/llms.txt

## 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.

## Links
- DOI: https://doi.org/10.3390/make5040083
- OpenAlex: https://openalex.org/W4388823657
- PDF: https://www.mdpi.com/2504-4990/5/4/83/pdf?version=1700497489
- JSON API: https://science-database.com/api/v1/technology/computer-vision

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Paper ID: oa-W4388823657 | Hub: computer-vision