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Yolov11 License Plate Detection

Developed by morsetechlab
A license plate detection model fine-tuned based on YOLOv11, optimized for license plate recognition tasks and supporting multiple model variants.
Downloads 175
Release Time : 5/3/2025

Model Overview

This model is a fine-tuned version of YOLOv11, specifically designed for license plate detection tasks and suitable for scenarios such as intelligent parking and traffic monitoring.

Model Features

Multiple model variants
Provide five model variants: n, s, m, l, and x to meet different scenario requirements.
High-precision detection
The precision rate reaches 0.9893, the recall rate reaches 0.9508, and the mAP@50 reaches 0.9813.
Cross-platform support
Support PyTorch and ONNX formats for easy deployment on different platforms.

Model Capabilities

License plate detection
Real-time image processing
Multi-size license plate recognition

Use Cases

Intelligent transportation
Intelligent parking system
Automatically detect license plates in the parking lot to achieve unmanned management.
Toll station automation
Automatically recognize the license plates of passing vehicles to improve traffic efficiency.
Public safety
Traffic monitoring and law enforcement
Automatically detect the license plates of illegal vehicles to assist traffic law enforcement.
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