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Pedestrian Age Recognition

Developed by NTQAI
A pedestrian age classification model fine-tuned based on BEiT architecture, achieving 80.73% accuracy on the evaluation set
Downloads 1,481
Release Time : 1/9/2023

Model Overview

This model is a pedestrian age classification model fine-tuned on the imagefolder dataset, based on the microsoft/beit-base-patch16-224-pt22k-ft22k pre-trained model. It is primarily used to recognize the age stage of pedestrians from images.

Model Features

High Accuracy
Achieves 80.73% classification accuracy on the evaluation set
Based on BEiT Architecture
Utilizes the advanced BEiT visual Transformer architecture for feature extraction
End-to-End Training
Supports a complete workflow from raw image input to age classification output

Model Capabilities

Pedestrian Age Recognition
Image Classification
Visual Feature Extraction

Use Cases

Smart Surveillance
Mall Customer Flow Analysis
Analyze the distribution of customers in different age groups within a mall
Public Safety
Missing Child Identification
Identify children of specific age groups in public places
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