Yolov5n Blood Cell
A lightweight blood cell object detection model based on the YOLOv5n architecture, optimized for medical image analysis
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Release Time : 12/31/2022
Model Overview
This model utilizes the YOLOv5n architecture and is optimized for blood cell detection tasks, capable of accurately identifying and locating various types of cells in blood samples
Model Features
High-precision Detection
Achieves 92.3% mAP@0.5 accuracy in blood cell detection tasks
Lightweight Architecture
Designed based on YOLOv5n, the model is compact with fast inference speed
Medical Specialization
Specifically optimized for blood cell detection tasks, suitable for medical image analysis
Model Capabilities
Blood Cell Detection
Object Localization
Medical Image Analysis
Use Cases
Medical Diagnosis
Blood Cell Counting
Automatically detects and counts various types of cells in blood samples
Can replace traditional manual counting methods, improving efficiency and accuracy
Abnormal Cell Detection
Identifies abnormal or diseased cells in blood samples
Assists doctors in disease diagnosis
Medical Research
Blood Sample Analysis
Automated analysis of large-scale blood samples
Accelerates medical research progress
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