scholarly journals Mask Detection Application

2021 ◽  
Vol 9 (VII) ◽  
pp. 2935-2962
Author(s):  
Dr. L. Srinivasan
Keyword(s):  
Data Base ◽  
Facial Recognition ◽  
Face Mask ◽  
Identification Number ◽  
Huge Data ◽  
Proper Face ◽  
Tools And Techniques

With covid-19 being on the Rise we needed an efficient way to take care of the growing coronavirus cases. Various Tools and techniques are used to curb the spread of the virus this project aims to develop an application that helps in detecting and identifying the individuals that are not wearing a proper face mask when out in public. The photograph is taken and uploaded there is a huge data base of individual's information for example their name, semester, identification number, university seat number, branch etc. the photographs are run through the database to identify the persons without wearing a mask using facial recognition in this application can be very effectively used to curb the cases of Corona since it identifies the mask defaulters and thus we can help in controlling the infection and the spread of the virus and save many lives.

scholarly journals Facial Recognition System for People with and without Face Mask in Times of the COVID-19 Pandemic

2021 ◽  
Vol 13 (12) ◽  
pp. 6900
Author(s):  
Jonathan S. Talahua ◽  
Jorge Buele ◽  
P. Calvopiña ◽  
José Varela-Aldás
Keyword(s):  
Facial Recognition ◽  
Face Mask ◽  
Recognition System ◽  
Classification Model ◽  
World Health ◽  
The Face ◽  
Recognition Systems ◽  
Facial Recognition System ◽  
Health Organization ◽  
Face Detector

In the face of the COVID-19 pandemic, the World Health Organization (WHO) declared the use of a face mask as a mandatory biosafety measure. This has caused problems in current facial recognition systems, motivating the development of this research. This manuscript describes the development of a system for recognizing people, even when they are using a face mask, from photographs. A classification model based on the MobileNetV2 architecture and the OpenCv’s face detector is used. Thus, using these stages, it can be identified where the face is and it can be determined whether or not it is wearing a face mask. The FaceNet model is used as a feature extractor and a feedforward multilayer perceptron to perform facial recognition. For training the facial recognition models, a set of observations made up of 13,359 images is generated; 52.9% images with a face mask and 47.1% images without a face mask. The experimental results show that there is an accuracy of 99.65% in determining whether a person is wearing a mask or not. An accuracy of 99.52% is achieved in the facial recognition of 10 people with masks, while for facial recognition without masks, an accuracy of 99.96% is obtained.

scholarly journals COVID-19 Authorized Entry with Face Mask Detection using Raspberry Pi

2021 ◽  
Vol 9 (VI) ◽  
pp. 1862-1867
Author(s):  
Anju Ajay
Keyword(s):  
Large Scale ◽  
Facial Recognition ◽  
Face Mask ◽  
Raspberry Pi ◽  
Wireless Internet ◽  
Great Demand ◽  
Embedded Device ◽  
Internet Connection ◽  
Battery Power ◽  
Python Programming

There are no effective face mask detection applications in the current COVID-19 scenario, which is in great demand for transportation, densely populated places, residential districts, large-scale manufacturers, and other organizations to ensure safety. In addition, the lack of big datasets of photographs with mask has made this task more difficult. With the use of Python programming, the Open CV library, Keras, and tensor flow, this project presents a way for recognizing persons without wearing a face mask using the facial recognition methodology. This is a self-contained embedded device that was created with the Raspberry Pi Electronic Development Board and runs on battery power. We make use of a wireless internet connection using USB modem. In comparison to other existing systems, our proposed method is more effective, reliable, and consumes significantly less data and electricity

scholarly journals Analyzation and Comparison of Cloud Computing and Data Mining Techniques: Big Data and Impact of Blockchain

2021 ◽  
Vol 9 (11) ◽  
pp. 712-721
Author(s):  
Adarsh Bhandari
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Analytics ◽  
Scale Up ◽  
Big Data Analytics ◽  
Multiple Sources ◽  
Huge Data ◽  
Amazon Web Services ◽  
Tools And Techniques ◽  
The Impact

Abstract: With the rapid escalation of data driven solutions, companies are integrating huge data from multiple sources in order to gain fruitful results. To handle this tremendous volume of data we need cloud based architecture to store and manage this data. Cloud computing has emerged as a significant infrastructure that promises to reduce the need for maintaining costly computing facilities by organizations and scale up the products. Even today heavy applications are deployed on cloud and managed specially at AWS eliminating the need for error prone manual operations. This paper demonstrates about certain cloud computing tools and techniques present to handle big data and processes involved while extracting this data till model deployment and also distinction among their usage. It will also demonstrate, how big data analytics and cloud computing will change methods that will later drive the industry. Additionally, a study is presented later in the paper about management of blockchain generated big data on cloud and making analytical decision. Furthermore, the impact of blockchain in cloud computing and big data analytics has been employed in this paper. Keywords: Cloud Computing, Big Data, Amazon Web Services (AWS), Google Cloud Platform (GCP), SaaS, PaaS, IaaS.

Design, Implementation, and Characterization of a Proper Face Mask Usage Classification Model

2021 ◽  
Author(s):  
Robin Jerome Reyes ◽  
Geosef Viktor Uy ◽  
Gabriel Nicolas Minamedez ◽  
Macario Cordel
Keyword(s):  
Face Mask ◽  
Classification Model ◽  
Proper Face

scholarly journals Evidence for the Galactic Bar from the Two Color Photometry of the Bulge Red Clump Stars

1996 ◽  
Vol 169 ◽  
pp. 103-109
Author(s):  
K. Z. Stanek ◽  
M. Mateo ◽  
A. Udalski ◽  
M. Szymański ◽  
J. Kałużny ◽  
...  
Keyword(s):  
Data Base ◽  
Gravitational Lensing ◽  
Galactic Bulge ◽  
Gravitational Microlensing ◽  
Huge Data ◽  
Red Clump

The Optical Gravitational Lensing Experiment (OGLE, Udalski et al. 1994a; Paczynski et al. 1994b – these proceedings; and references therein) is an extensive photometric search for the rare cases of gravitational microlensing of Galactic bulge stars by foreground objects. It provides a huge data base (Szymański & Udalski 1993), from which color-magnitude diagrams have been compiled (Udalski et al. 1993, 1994b). Here we discuss the use a of well-defined population of bulge red clump stars to investigate the presence of the bar in our Galaxy. The results of our earlier studies are described by Stanek et al. (1994).

scholarly journals Pattern of hygiene practices among health care workers during the COVID-19 pandemic: a tertiary health care experience from Central Kerala

2021 ◽  
Vol 8 (6) ◽  
pp. 2952
Author(s):  
Susan John ◽  
Suremya A. Subrahmanian ◽  
Rina T. Xavier
Keyword(s):  
Health Care ◽  
Face Mask ◽  
Clinical Staff ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Care Experience ◽  
Hygiene Practices ◽  
Increased Risk ◽  
The Difference ◽  
Proper Face

Background: The recent COVID-19 pandemic has highlighted the relevance of following hygiene practices across all sectors of healthcare workers. Disparities in the correct practices among clinical and para clinical cadres of HCWs predispose to increased risk of infection. A survey was conducted to assess the hand and respiratory hygiene practices across the hospital.Methods: A cross sectional survey was conducted through a self-administered questionnaire across an online platform with questions on hand hygiene, mask and surface contamination related practices. Staff were grouped as clinical and para clinical for comparison of these practices.Results: Among the 501 respondents, 83.4% were females with a mean age of 30.78±8.48 years. Nursing staff were the majority (57.88%) followed by nonclinical and para clinical staff (20.77%). Of the study population, 96.6% performed hand wash and 97.2% refrained from giving handshakes in the previous hour. Over 60% maintained proper face mask practices. Undoing the lower tie of the mask first, was answered by 76.67% while 7.2% felt the sequence was irrelevant. Touching common surfaces were avoided by 46.3% of them, while 95% immersed their hospital attire in soap and water for 15 minutes. It was seen that a greater proportion of clinical staff had better practices when compared to para clinical and the difference statistically significant. There was no significant variation of practices with age.Conclusions: Focussed monitoring and motivation can help in improving hygiene practices among all cadres of HCWs.

scholarly journals Texton Based Image Retrieval Using Indexed LBP Transitions

2014 ◽  
Vol 13 (12) ◽  
pp. 5286-5300 ◽  
Author(s):  
A. Srinivasa Rao ◽  
V.Venkata Krishna ◽  
Prof.YKSundara Krishna
Keyword(s):  
Image Retrieval ◽  
Data Base ◽  
Local Binary Pattern ◽  
Texture Features ◽  
Experimental Result ◽  
Texture Image ◽  
Huge Data ◽  
Proposed Model ◽  
Occurrence Matrix ◽  
Rotationally Invariant

The present paper derived a new model of texture image retrieval by integrating the transitions on Local Binary Pattern (LBP) with textons and Grey Level Co-occurrence Matrix (GLCM). The present paper initially derived transitions that occur from 0 to 1 or 1 to 0 in circular manner on LBP. The transitions reduce the 256 LBP codes into five texture features. This reduces the lot of complexity. The LBP codes are rotationally variant. The proposed circular transitions on LBP are rotationally invariant. Textons,which represents the local relationships,are detected on this. The GLCM features are evaluated on the texton based image for efficient image retrieval. The proposed method is experimented on a huge data base of textures collected from Google data base. The experimental result indicates the efficiency of the proposed model.

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