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Ivan Hartono
Program Studi Teknik Informatika, Universitas Kristen Petra Surabaya
Computer Science & IT

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Deteksi Masker Wajah dengan Metode Convolutional Neural Network Ivan Hartono; Agustinus Noertjahyana; Leo Willyanto Santoso
Jurnal Infra Vol 10, No 1 (2022)
Publisher : Universitas Kristen Petra

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Abstract

The computer must be able to recognize the area which is a face object in the image in order to facilitate the detection of face masks used by humans. Deep learning is artificial intelligence with simple representations that have hidden layers to process data that can build complex concepts. Deep learning can be trained to detect an object and classify objects. There are many deep learning algorithms that can be used for the model recognition process, for example for object classification using MobileNet, VGGNet, DenseNet, GoogLeNet, AlexNet, and others while for object detection you can use You Only Look Once, SSD Resnet, Multi-task Cascaded Convolutional Neural Network (MTCNN), HyperFace and others. The object detection system can use two combinations of algorithms, namely the object classification method and the object detection method. The method for recognizing mask objects on human faces is CNN (Convolutional Neural Network).The CNN method is the development of the Multilayer Perceptron which is designed to process two-dimensional data. CNN method is very good in processing spatial data and classifying objects [1]. After training the model with VGGNet, the next method is to detect an object using the SSD ResNet module.
Co-Authors Agustinus Noertjahyana Leo Willyanto Santoso