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Yolov5n V7.0

Developed by fcakyon
YOLOv5n-v7.0 is a lightweight object detection model based on the YOLOv5 architecture, suitable for real-time object detection tasks.
Downloads 82
Release Time : 12/13/2022

Model Overview

YOLOv5n-v7.0 is an efficient object detection model based on the YOLOv5 architecture, supporting detection of multiple object categories and suitable for computer vision tasks.

Model Features

Lightweight design
The model has a small size, making it suitable for running on devices with limited resources.
Real-time detection
Supports real-time object detection, ideal for applications requiring quick responses.
High accuracy
Performs well on the COCO dataset, accurately detecting multiple object categories.

Model Capabilities

Object detection
Real-time inference
Multi-category recognition

Use Cases

Security surveillance
Real-time monitoring
Used for real-time object detection in surveillance videos, identifying suspicious objects or behaviors.
Enhances the intelligence level of surveillance systems, reducing manual intervention.
Autonomous driving
Road object detection
Detects vehicles, pedestrians, traffic signs, and other objects on the road.
Improves the environmental perception capabilities of autonomous driving systems.
Industrial inspection
Defect detection
Detects defects or anomalies in industrial products.
Enhances the efficiency of product quality control.
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