# YOLOv5, YOLOv8 and YOLOv10: The Go-To Detectors for Real-time Vision

arXiv: https://arxiv.org/abs/2407.02988 · HTML: https://mlsanity.com/paper/2407.02988/

## Key facts

- Cited by 12 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 27 references that are in the map.
- First posted on arXiv 3 Jul 2024.

## Builds on (most cited first, 2 of 2)

- [YOLOv10: Real-Time End-to-End Object Detection](https://mlsanity.com/paper/2405.14458/) (2024)
- [YOLOv1 to YOLOv10: A comprehensive review of YOLO variants and their application in the agricultural domain](https://mlsanity.com/paper/2406.10139/) (2024)

## Built on by (most cited first, 12 of 12)

- [IMAGGarment: Fine-Grained Garment Generation for Controllable Fashion Design](https://mlsanity.com/paper/2504.13176/) (2025)
- [Enhanced Self-Checkout System for Retail Based on Improved YOLOv10](https://mlsanity.com/paper/2407.21308/) (2024)
- [LLM-Guided Evolution: An Autonomous Model Optimization for Object Detection](https://mlsanity.com/paper/2504.02280/) (2025)
- [KhmerST: A Low-Resource Khmer Scene Text Detection and Recognition Benchmark](https://mlsanity.com/paper/2410.18277/) (2024)
- [Deep Learning-Based Multi-Object Tracking: A Comprehensive Survey from Foundations to State-of-the-Art](https://mlsanity.com/paper/2506.13457/) (2025)
- [A Comprehensive Evaluation of YOLO-based Deer Detection Performance on Edge Devices](https://mlsanity.com/paper/2509.20318/) (2025)
- [RT-Focuser: A Real-Time Lightweight Model for Edge-side Image Deblurring](https://mlsanity.com/paper/2512.21975/) (2025)
- [Surveying You Only Look Once (YOLO) Multispectral Object Detection Advancements, Applications And Challenges](https://mlsanity.com/paper/2409.12977/) (2024)
- [STAG-VIO: Stabilized Prompt-to-Geometry Interface for Robust Dynamic Visual--Inertial Odometry](https://mlsanity.com/paper/2411.19289/) (2024)
- [A Comprehensive Dataset for Underground Miner Detection in Diverse Scenario](https://mlsanity.com/paper/2506.21451/) (2025)
- [Real-Time Fish Detection in Indonesian Marine Ecosystems Using Lightweight YOLOv10-nano Architecture](https://mlsanity.com/paper/2509.17406/) (2025)
- [A 360-degree Multi-camera System for Blue Emergency Light Detection Using Color Attention RT-DETR and the ABLDataset](https://mlsanity.com/paper/2603.05058/) (2026)

## Abstract (arXiv)

This paper presents a comprehensive review of the evolution of the YOLO (You Only Look Once) object detection algorithm, focusing on YOLOv5, YOLOv8, and YOLOv10. We analyze the architectural advancements, performance improvements, and suitability for edge deployment across these versions. YOLOv5 introduced significant innovations such as the CSPDarknet backbone and Mosaic Augmentation, balancing speed and accuracy. YOLOv8 built upon this foundation with enhanced feature extraction and anchor-free detection, improving versatility and performance. YOLOv10 represents a leap forward with NMS-free training, spatial-channel decoupled downsampling, and large-kernel convolutions, achieving state-of-the-art performance with reduced computational overhead. Our findings highlight the progressive enhancements in accuracy, efficiency, and real-time performance, particularly emphasizing their applicability in resource-constrained environments. This review provides insights into the trade-offs between model complexity and detection accuracy, offering guidance for selecting the most appropriate YOLO version for specific edge computing applications.