Deteksi Wajah Bermasker Menggunakan Deep Neural Network dan Tensorflow

Rian Dwi Yulian Prakoso, Sriyati Sriyati, Nabil Makarim, Farrel Witamajaya

Abstract


The use of face masks is an important part of life in the midst of the Covid-19 pandemic which has been designated as a global pandemic, people are urged to cover their faces when in public areas to avoid the spread of the virus. The use of these face masks has raised serious questions regarding face detection systems. This study used Deep Neural Network and Tensorflow methods to detect faces both using masks and without masks. This study used two datasets, a face collection dataset without a mask and a face group using a mask. The result of this study was the detection of faces with masks trained on the dataset achieved 98% accuracy in training, and for testing got 100% accuracy on faces without masks, and 99.99% accuracy for face with mask. 


Keywords


deep neural network, tensorflow, face detection, with masks and without masks

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References


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DOI: http://dx.doi.org/10.30646/sinus.v21i1.629

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