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About Face Mask Detection For Covid - 19 Pandemic Using Pytorch in Deep Learning
This document summarizes a research paper that proposes a deep learning approach for face mask detection during the COVID-19 pandemic. The approach uses PyTorch to train a MobileNetV2 convolutional neural network model on images of people with and without masks. It then applies the trained model to detect masks in images and video streams in real-time. The goal is to identify people following or not following mask guidelines to help curb the spread of the virus. The paper reviews other related works on masked face detection and recognition. It then outlines the proposed approach, which involves preprocessing the dataset, training the MobileNetV2 model, serializing the trained classifier, and applying it to detect masks in new images and video streams.
Detailed Information
| Author: | ['Orhun Küpeli'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 11 |
| Language: | English |
| Format: | |
| Price: | FREE |
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