ConvNeXt-FaceMask-Finetuned Open Source Face Mask Detection Model - Ultra-high Accuracy for Precise Face Mask Identification

Convnext FaceMask Finetuned

Developed by AkshatSurolia

A mask detection model using the ConvNeXt architecture, trained on the Face-Mask18K dataset with an accuracy rate of 99.61%.

Downloads 26

Release Time : 3/2/2022

Model Overview

This model is used to detect whether people in images are wearing masks, suitable for epidemic prevention monitoring in public places.

High accuracy

Achieves 99.61% accuracy on the evaluation dataset.

Efficient training

Training sample processing speed reaches 14.075 samples/second, evaluation speed reaches 43.079 samples/second.

Modern architecture

Utilizes ConvNeXt, a modern convolutional neural network architecture with excellent performance.

Image classification

Mask detection

Public health

Public place epidemic prevention monitoring

Used to detect whether people in public places are wearing masks

Enables automated monitoring with 99.61% accuracy

Intelligent security

Access control systems

Integrated into access control systems to ensure mask-wearing before entering specific areas

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