Face mask detection using convolution neural network
- URL: http://arxiv.org/abs/2106.05728v1
- Date: Thu, 10 Jun 2021 13:18:57 GMT
- Title: Face mask detection using convolution neural network
- Authors: Riya Shah Rutva Shah
- Abstract summary: This paper proposes a method to detect the face mask is put on or not for offices, or any other work place with a lot of people coming to work.
The model is trained on a real world dataset and tested with live video streaming with a good accuracy.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: In the recent times, the Coronaviruses that are a big family of different
viruses have become very common, contagious and dangerous to the whole human
kind. It spreads human to human by exhaling the infection breath, which leaves
droplets of the virus on different surface which is then inhaled by other
person and catches the infection too. So it has become very important to
protect ourselves and the people around us from this situation. We can take
precautions such as social distancing, washing hands every two hours, using
sanitizer, maintaining social distance and the most important wearing a mask.
Public use of wearing a masks has become very common everywhere in the whole
world now. From that the most affected and devastating condition is of India
due to its extreme population in small area. This paper proposes a method to
detect the face mask is put on or not for offices, or any other work place with
a lot of people coming to work. We have used convolutional neural network for
the same. The model is trained on a real world dataset and tested with live
video streaming with a good accuracy. Further the accuracy of the model with
different hyper parameters and multiple people at different distance and
location of the frame is done.
Related papers
- Detection of a facemask in real-time using deep learning methods:
Prevention of Covid 19 [37.265888777364594]
The novel-coronavirus disease (Covid-19) has already affected our day-to-day life as well as world trade movements.
By the end of April 2021, the world has recorded 144,358,956 confirmed cases of novel-coronavirus disease (Covid-19) including 3,066,113 deaths according to the world health organization (WHO)
We propose a technique using deep learning that works for single and multiple people in a frame recorded via webcam in still or in motion.
arXiv Detail & Related papers (2024-01-28T14:45:52Z) - A Survey on Masked Facial Detection Methods and Datasets for Fighting
Against COVID-19 [64.88701052813462]
Coronavirus disease 2019 (COVID-19) continues to pose a great challenge to the world since its outbreak.
To fight against the disease, a series of artificial intelligence (AI) techniques are developed and applied to real-world scenarios.
In this paper, we primarily focus on the AI techniques of masked facial detection and related datasets.
arXiv Detail & Related papers (2022-01-13T03:28:20Z) - Adversarial Mask: Real-World Adversarial Attack Against Face Recognition
Models [66.07662074148142]
We propose a physical adversarial universal perturbation (UAP) against state-of-the-art deep learning-based facial recognition models.
In our experiments, we examined the transferability of our adversarial mask to a wide range of deep learning models and datasets.
We validated our adversarial mask effectiveness in real-world experiments by printing the adversarial pattern on a fabric medical face mask.
arXiv Detail & Related papers (2021-11-21T08:13:21Z) - Indian Masked Faces in the Wild Dataset [86.79402670904338]
We present a novel textbfIndian Masked Faces in the Wild (IMFW) dataset which contains images with variations in pose, illumination, resolution, and the variety of masks worn by the subjects.
We have also benchmarked the performance of existing face recognition models on the proposed IMFW dataset.
arXiv Detail & Related papers (2021-06-17T17:23:54Z) - Masked Face Recognition using ResNet-50 [0.0]
We are facing an elusive health crisis with the emergence of COVID-19 disease of the coronavirus family.
Public health officials have mandated the use of face masks which can reduce disease transmission by 65%.
This paper investigates the same problem by developing a deep learning based model capable of accurately identifying people with face-masks.
arXiv Detail & Related papers (2021-04-19T01:09:47Z) - Contrastive Context-Aware Learning for 3D High-Fidelity Mask Face
Presentation Attack Detection [103.7264459186552]
Face presentation attack detection (PAD) is essential to secure face recognition systems.
Most existing 3D mask PAD benchmarks suffer from several drawbacks.
We introduce a largescale High-Fidelity Mask dataset to bridge the gap to real-world applications.
arXiv Detail & Related papers (2021-04-13T12:48:38Z) - A Computer Vision System to Help Prevent the Transmission of COVID-19 [79.62140902232628]
The COVID-19 pandemic affects every area of daily life globally.
Health organizations advise social distancing, wearing face mask, and avoiding touching face.
We developed a deep learning-based computer vision system to help prevent the transmission of COVID-19.
arXiv Detail & Related papers (2021-03-16T00:00:04Z) - BinaryCoP: Binary Neural Network-based COVID-19 Face-Mask Wear and
Positioning Predictor on Edge Devices [63.56630165340053]
Face masks offer an effective solution in healthcare for bi-directional protection against air-borne diseases.
CNNs offer an excellent solution for face recognition and classification of correct mask wearing and positioning.
CNNs can be used at entrances to corporate buildings, airports, shopping areas, and other indoor locations, to mitigate the spread of the virus.
arXiv Detail & Related papers (2021-02-06T00:14:06Z) - An Automatic System to Monitor the Physical Distance and Face Mask
Wearing of Construction Workers in COVID-19 Pandemic [0.0]
The World Health Organization recommends wearing a face mask and practicing physical distancing to mitigate the virus's spread.
This paper developed a computer vision system to automatically detect the violation of face mask wearing and physical distancing among construction workers.
arXiv Detail & Related papers (2021-01-05T06:53:41Z) - Face Mask Assistant: Detection of Face Mask Service Stage Based on
Mobile Phone [35.26022029969275]
Syndrome coronaviruses 2 (SARS-CoV-2), the cause of COVID-19, can be transmitted by small respiratory droplets.
To curb its spread at the source, wearing masks is a convenient and effective measure.
We propose a detection system based on the mobile phone.
arXiv Detail & Related papers (2020-10-09T08:49:52Z) - Multi-Stage CNN Architecture for Face Mask Detection [0.0]
We introduce a Deep Learning based system that can detect instances where face masks are not used properly.
Our system consists of a dual-stage Convolutional Neural Network (CNN) architecture capable of detecting masked and unmasked faces.
This will help track safety violations, promote the use of face masks, and ensure a safe working environment.
arXiv Detail & Related papers (2020-09-16T12:23:21Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.