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Yolov8m Forklift Detection
An object detection model based on YOLOv8m, specifically designed for detecting forklifts and personnel, suitable for safety monitoring in industrial scenarios.
Downloads 294
Release Time : 1/22/2023
Model Overview
This model is an object detection model based on the YOLOv8 architecture, specifically designed to detect forklifts and personnel in industrial environments. It can help achieve workplace safety monitoring and automated management.
Model Features
High-precision Detection
Achieves 84.59% mAP@0.5 accuracy on the forklift object detection dataset.
Multi-class Detection
Capable of detecting both forklifts and personnel simultaneously.
Industrial Scenario Optimization
Specifically optimized for forklift detection in industrial environments.
Model Capabilities
Object detection in images
Forklift recognition
Personnel detection
Industrial scenario analysis
Use Cases
Industrial Safety
Workplace Safety Monitoring
Real-time monitoring of forklift and personnel positions in industrial settings to prevent collision accidents.
Enhances workplace safety and reduces occupational injuries.
Automated Logistics Management
Tracking forklift positions and activities in automated warehouses.
Optimizes logistics efficiency and enables intelligent management.
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