scholarly journals AI Enabled Face Mask Detector

2021 ◽  
Vol 9 (VI) ◽  
pp. 2980-2986
Author(s):  
Shivraj Patil
Keyword(s):  
Machine Learning ◽  
Global Health ◽  
Image Classification ◽  
Learning Algorithm ◽  
Face Mask ◽  
Classification Method ◽  
Machine Learning Algorithm ◽  
Health Crisis ◽  
The Face

Covid-19 pandemic is causing a global health crisis. To battle against the virus everyone should wear a face mask. The face mask detector in this study is developed with a machine learning algorithm called MobileNetV2 which is an image classification method. The steps to build the model are collecting the data, pre-processing, split the data, testing the model and implement the model.

scholarly journals HOW CAN MACHINE LEARNING HELP THE AUTHORITIES?

2021 ◽  
Vol 2020 (1) ◽  
pp. 370-376
Author(s):  
Samuel Ady Sanjaya ◽  
Suryo Adi Rakhmawan
Keyword(s):  
Machine Learning ◽  
Learning Algorithm ◽  
Action Planning ◽  
Face Mask ◽  
Public Place ◽  
Communication Tool ◽  
Health Crisis ◽  
Surveillance Camera ◽  
Proposed Model ◽  
The Face

Corona Virus Desease (COVID-19) pandemic is causing health crisis in every region in the world, especially in Indonesia. One of the effective methods against the virus is wearing face mask in public place as the regulation made by the authorities. This paper introduces face mask detection that can be used by the authorities to make mitigation, evaluation, prevention, and action planning against COVID-19. On the other hand, this solution can be used as communication tool to evaluate people’s habit on wearing face mask. The face mask recognition in this study is developed with machine learning algorithm through the image classification method: MobileNetv2. The proposed model can be integrated with surveillance camera to impede the Covid-19 transmission by allowing the detection of people who are not wearing face mask. After the training, validation, and testing phase, the model can provide the percentage of people using face mask in some cities with high accuracy. The data produced also have a strong correlation to the vigilance index of COVID-19.

scholarly journals Image Classification using CNN and Machine Learning

2019 ◽  
pp. 575-580
Author(s):  
G. Keerthi Devipriya ◽  
E. Chandana ◽  
B. Prathyusha ◽  
T. Seshu Chakravarthy
Keyword(s):  
Machine Learning ◽  
Image Classification ◽  
Learning Algorithm ◽  
Machine Learning Algorithm ◽  
Data Set ◽  
Training Models ◽  
Classification Of Images ◽  
Respective Category

Here by in this paper we are interested for classification of Images and Recognition. We expose the performance of training models by using a classifier algorithm and an API that contains set of images where we need to compare the uploaded image with the set of images available in the data set that we have taken. After identifying its respective category the image need to be placed in it. In order to classify images we are using a machine learning algorithm that comparing and placing the images.

scholarly journals Real Time Face Recognition in Group Images using LBPH

2019 ◽  
Vol 8 (2) ◽  
pp. 1362-1367
Keyword(s):  
Machine Learning ◽  
Computer Vision ◽  
Face Recognition ◽  
Real Time ◽  
Learning Algorithm ◽  
Machine Learning Algorithm ◽  
Testing Dataset ◽  
Negative Images ◽  
The Face ◽  
Haar Cascade

Face recognition is a beneficial work in computer vision based applications. The goal of the proposed system is to provide complete face recognitions system capable of working a group of images. The faces are detected and verified the identity of an individual using a machine learning algorithm. The haar cascade detects the face from a group of images for training and testing dataset. The dataset contained positive and negative images for training and testing. The LBPH algorithm recognizes the faces from input images. The proposed system detects and recognizes faces with 98% accuracy

scholarly journals Voice Controlled Personal Assistive Bot with Object Detection

2021 ◽  
Vol 12 (4) ◽  
pp. 578-584
Author(s):  
S. A. Sivasankari, Et. al.
Keyword(s):  
Machine Learning ◽  
Face Recognition ◽  
Learning Algorithm ◽  
Raspberry Pi ◽  
Machine Learning Algorithm ◽  
Primary Reason ◽  
Person Detection ◽  
Personal Assistance ◽  
Human Voice ◽  
The Face

Currently innovation has made our lives simpler for individuals. Be that as it may, from this innovation, certain gatherings of individuals need more assistance and backing for old or handicap individuals. This innovation can make a method of having a typical life. Thus, we zeroed in on the idea of an individual colleague robot. The fundamental objectisto supply helptodebilitated people.ThisPerson alassistive Bot help to decrease the manual endeavors being put by people in their everyday errands. The intention is to execute a specialized work that is voice controlling one which can act as a PA that can performvarious errands or administrations for a person.This is uncommonly intended for this group of people asits primary reason for existing is to supply help to relate senior or debilitated individual. The human voice order is given to the mechanical right hand distantly,by utilizing a voice order.The automaton will perform different movements: Forward, Backward, Right, Left and start/stop activities. The robot can likewise peruse and perceive the letter sets and text and the words which are said by the person will check from the google dictionary and printasatext.The capability of the robotisto detect the objects and relocate the m from one place to another and includes the face recognition. So, our main ideology is to create a personal assistance bot, which is capable of handling small objects. We are planning to make the bot consisting of four wheels and an arm placed on top. Using Raspberry Pi, we are communicating the sensors and motors throughour voice commands. Smart assistants like Google for android,Sir ifor Apple,Corton a for Microsoft,the seassistive gives us a platform to communicate to a bot. Asweare programming on Python, Amodule name Pyaudio will helpto communicate with a bot and having the extra feature like ‘Speechto Text’.And we would like to add an extra feature like object and person detection. A Camera module will be installed for capturing video and recognize the Humans and objects carried out with Machine Learning Algorithm

Machine Learning Algorithm to Predict Early Complications after Brain Tumor Surgery

2018 ◽  
Author(s):  
C.H.B. van Niftrik ◽  
F. van der Wouden ◽  
V. Staartjes ◽  
J. Fierstra ◽  
M. Stienen ◽  
...  
Keyword(s):  
Machine Learning ◽  
Brain Tumor ◽  
Learning Algorithm ◽  
Machine Learning Algorithm ◽  
Tumor Surgery ◽  
Early Complications ◽  
Brain Tumor Surgery

Feature extraction and prediction of Dengue Outbreaks

2020 ◽  
pp. 216-222
Author(s):  
Kunal Parikh ◽  
Tanvi Makadia ◽  
Harshil Patel
Keyword(s):  
Public Health ◽  
Machine Learning ◽  
Developing Countries ◽  
Feature Extraction ◽  
Predictive Analytics ◽  
Learning Algorithm ◽  
Machine Learning Algorithm ◽  
Health Concerns ◽  
The World ◽  
Dengue Outbreaks

Dengue is unquestionably one of the biggest health concerns in India and for many other developing countries. Unfortunately, many people have lost their lives because of it. Every year, approximately 390 million dengue infections occur around the world among which 500,000 people are seriously infected and 25,000 people have died annually. Many factors could cause dengue such as temperature, humidity, precipitation, inadequate public health, and many others. In this paper, we are proposing a method to perform predictive analytics on dengue’s dataset using KNN: a machine-learning algorithm. This analysis would help in the prediction of future cases and we could save the lives of many.

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