Convnext FaceMask Finetuned
C
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.
Model Features
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.
Model Capabilities
Image classification
Mask detection
Use Cases
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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