scholarly journals Improved Facial Recognition for Attendance Systems

2020 ◽  
pp. 456-467
Author(s):  
Hari Purnapatre ◽  
Satvik Shukla ◽  
Shravan Gangishetti ◽  
Harshal Bohra
Keyword(s):  
Facial Recognition ◽  
Online Database ◽  
Primary Method ◽  
Automated Systems ◽  
Major Focus ◽  
Person Identification ◽  
Fingerprint Verification ◽  
Non Invasive ◽  
Fully Automatic ◽  
Human Support

Attendance is an important part of educational life. The attendance methodology which exists currently is either totally manual or requires some human assistance. In traditional methods, the teacher manually marks the attendance of each student on paper. There are many flaws in this method. As the process is manual there is a chance of error in the marking of attendance. Similarly, marking of false attendance by the students is also possible. Moreover, the attendance is then required to be updated in the online database of the institute through which it is accessible to the students. Also, after every month a report of all the students is to be generated. This overall process is cumbersome and time consuming. There also exist some automated systems for attendance like fingerprint verification and RFID but they also require some human support. Here, the automated attendance system using facial recognition plays an important role which requires no human intervention and is fully automatic. Face recognition has always remained a major focus of research because of its non-invasive nature and because it is people's primary method of person identification.

scholarly journals Three-dimensional simplified electrodynamic model of the human chest

2019 ◽  
Vol 30 ◽  
pp. 13006 ◽  
Author(s):  
Alexander Dem'yanenko ◽  
Yaroslav Nevstruev ◽  
Olga Semernik
Keyword(s):  
Experimental Study ◽  
Electromagnetic Waves ◽  
Three Dimensional ◽  
High Tech ◽  
Automated Systems ◽  
Electrodynamic Model ◽  
Non Invasive ◽  
Healthy State ◽  
Bronchopulmonary Diseases

The results of the development of an accessible threedimensional electrodynamic model of the human chest in a healthy state and in the presence of various pathologies caused by bronchopulmonary diseases are presented. Simulation and experimental study of the propagation of electromagnetic waves in the human chest has been carried out with the aim of developing high-tech harmless non-invasive methods, devices and automated systems for diagnosing diseases of the bronchopulmonary system based on modern microwave technologies.

scholarly journals Recognition of Gender using Gait Energy Image Projections Based on Random Forest Classifier

2019 ◽  
Vol 8 (12) ◽  
pp. 1518-1523
Keyword(s):  
Performance Metrics ◽  
Ensemble Classifier ◽  
Person Identification ◽  
Projection Model ◽  
Non Invasive ◽  
Second Stage ◽  
Gait Energy Image ◽  
Image Projections ◽  
The Individual

Identification of gender is a very fascinating criterion in the present day scenario. Especially, in the surveillance applications, gender recognition is very beneficial. With the use of face, speech, voice and gait, the gender of a person can be determined. Non-contact, non-invasive and easily acquired at distance, gait analysis has attracted the interest of many researchers in the classification of gender. For the identification of gender, 2 stages of the methodology are used in our proposed work. A new descriptor called Gait energy image projection model(GPM) is proposed which highlights all the gender-related parameters. In the second stage of methodology, proposed descriptor GPM is fused with already existing descriptors like GEI and FED for enhanced performance. For classifying the gender, an Ensemble classifier called Random Forests is applied to the individual and fused descriptors and the results are evaluated. Two datasets are used for experimentation namely CASIA B and OU-ISIR datasets which are standard datasets for person identification and different performance metrics such as accuracy, precision, recall and error rate are evaluated.

scholarly journals Ulixes: Facial Recognition Privacy with Adversarial Machine Learning

2021 ◽  
Vol 2022 (1) ◽  
pp. 148-165
Author(s):  
Thomas Cilloni ◽  
Wei Wang ◽  
Charles Walter ◽  
Charles Fleming
Keyword(s):  
Machine Learning ◽  
State Of The Art ◽  
Facial Recognition ◽  
Clustering Methods ◽  
Non Invasive ◽  
Current State ◽  
Social Media Platforms ◽  
Adversarial Examples ◽  
The Cost ◽  
Photo Management

Abstract Facial recognition tools are becoming exceptionally accurate in identifying people from images. However, this comes at the cost of privacy for users of online services with photo management (e.g. social media platforms). Particularly troubling is the ability to leverage unsupervised learning to recognize faces even when the user has not labeled their images. In this paper we propose Ulixes, a strategy to generate visually non-invasive facial noise masks that yield adversarial examples, preventing the formation of identifiable user clusters in the embedding space of facial encoders. This is applicable even when a user is unmasked and labeled images are available online. We demonstrate the effectiveness of Ulixes by showing that various classification and clustering methods cannot reliably label the adversarial examples we generate. We also study the effects of Ulixes in various black-box settings and compare it to the current state of the art in adversarial machine learning. Finally, we challenge the effectiveness of Ulixes against adversarially trained models and show that it is robust to countermeasures.

scholarly journals Artificial Intelligence Based Person Identification Virtual Assistant

2019 ◽  
Vol 8 (2S11) ◽  
pp. 2315-2319
Keyword(s):  
Artificial Intelligence ◽  
Facial Recognition ◽  
Person Identification

In future all the electronic gadgets are operated by usingvirtualassistantwhichisanythingbutdifficulttogettoyetit needs in security. Project aims to provide security for virtual Assistant (VA) through facial recognition. The framework enables just approved users to access voice commands. By this we can get protection and security for virtual assistant (VA). Users can ask their help addresses like time, date and climate and find solution to the inquiries. This virtual assistant causes us to send email through voice commands and it also takes notes from voice commands with security. It gives access to the unapproved user to enlist with the required consent from the administrator. It is can exchange the pictures and documents just by using voice commands. It will take photographs using camera when we use the fitting voice commands. Various users in a family can get access to the virtual Assistant by facial recognition module.

scholarly journals A NON-INVASIVE TECHNIQUE USING TO MONITOR REPRODUCTIVE HORMONES IN COMMON PALM CIVETS

2018 ◽  
Vol 40 (3) ◽  
Author(s):  
Nguyen Thi Thu Hien ◽  
Nguyen Thi Phuong Thao ◽  
Nguyen Thanh Binh
Keyword(s):  
Estrous Cycle ◽  
Adult Female ◽  
Reproductive Hormones ◽  
Reproductive Season ◽  
Invasive Technique ◽  
Elisa Kit ◽  
Non Invasive ◽  
Fecal Steroid ◽  
Progesterone Metabolites ◽  
Fully Automatic

Fecal steroid assays have been used to study and provide information on the estrous cycle, pregnancy, re-estrus, reproductive season and therapeutic treatments in an expanded list of species. The purpose of the present study was to monitor the reproductive status of the Commom Palm Civets (Paradoxurus hermaphroditus) by fecal steroid assays. The study was conducted to collect 2635 fecal samples from 12 adult female civets in Dong Nai Biotechnology Center. The fecal contents of Progesterone (P4) and Estradiol (E2) were determinned by using fully automatic ELISA Dynex DS2 (Dynex, USA), Progesterone and Estradiol ELISA Kit (DRG International, Inc., Germany). In non-pregnancy civets, the concentrations of fecal E2 ranged from 0.05 to 7.01 μg/g df, with an average of 1.07 ± 0.84 μg/g and a peak of 3.22 ± 0.64 μg/g. Fecal progesterone metabolites were from 0.15 to 12.32 μg/g, the overall mean of the samples was 1.72 ± 2.16 μg/g. The period of change in E2 content averaging was 28.6 ± 2.29 days. During pregnancy, the P4 content in the stool ranged from 6.21-23.12 μg/g, an average of 15.17 ± 5.22 μg/g and approximately 5 to 7 fold higher than non-pregnant (P

scholarly journals Fully Automatic Retinal Vascular Tortuosity Assessment Integrating Domain-Related Information

Proceedings ◽  
2020 ◽  
Vol 54 (1) ◽  
pp. 32
Author(s):  
Lucía Ramos ◽  
Jorge Novo ◽  
José Rouco ◽  
Stéphanie Romeo ◽  
María D. Álvarez ◽  
...  
Keyword(s):  
Circulatory System ◽  
Fundus Image ◽  
Non Invasive ◽  
Vascular Tortuosity ◽  
Related Information ◽  
Fully Automatic ◽  
Anatomical Properties ◽  
Retinal Vascular Tortuosity ◽  
Arteries And Veins

The fundus of the eye is the only part of the human body that allows a direct non-invasive observation of the circulatory system. Retinal vascular tortuosity presents a valuable potential for diagnostic and treatment purposes of relevant vascular and systemic diseases. This work presents a computational metric for the tortuosity characterization that combines mathematical representations of the vessel segments with anatomical properties of the fundus image such as the vessel caliber, the distance to the optic disc, the distance to the fovea and the distinction between arteries and veins. The evaluation of the prognostic performance shows that the incorporation of the domain-related information allows a reliable characterization of the retinal vascular tortuosity that provides a better representation of the expert perception.

Analysis of urinary microRNAs in chronic kidney disease

2012 ◽  
Vol 40 (4) ◽  
pp. 875-879 ◽  
Author(s):  
Cristina Beltrami ◽  
Aled Clayton ◽  
Aled O. Phillips ◽  
Donald J. Fraser ◽  
Timothy Bowen
Keyword(s):  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Protein Quantification ◽  
Prognostic Indicators ◽  
Major Focus ◽  
Regulate Gene Expression ◽  
Disease Biomarkers ◽  
Non Invasive ◽  
Alternative Approach ◽  
Prognostic Tests

Kidney biopsy is the gold-standard diagnostic test for intrinsic renal disease, but requires hospital admission and carries a 3% risk of major complications. Current non-invasive prognostic indicators such as urine protein quantification have limited predictive value. Better diagnostic and prognostic tests for chronic kidney disease patients are a major focus for industry and academia, with efforts to date directed largely at urinary proteomic approaches. microRNAs constitute a recently identified class of endogenous short non-coding single-stranded RNA oligonucleotides that regulate gene expression post-transcriptionally. Quantification of urinary microRNAs offers an alternative approach to the identification of chronic kidney disease biomarkers.

scholarly journals Artificial Intelligence Based Person Identification Virtual Assistant

2019 ◽  
Vol 8 (2S8) ◽  
pp. 1702-1707
Keyword(s):  
Artificial Intelligence ◽  
Facial Recognition ◽  
Person Identification

In future all the electronic gadgets are operated by usingvirtualassistantwhichisanythingbutdifficulttogettoyetit needs in security. Project aims to provide security for virtual Assistant (VA) through facial recognition. The framework enables just approved users to access voice commands. By this we can get protection and security for virtual assistant (VA). Users can ask their help addresses like time, date and climate and find solution to the inquiries. This virtual assistant causes us to send email through voice commands and it also takes notes from voice commands with security. It gives access to the unapproved user to enlist with the required consent from the administrator. It is can exchange the pictures and documents just by using voice commands. It will take photographs using camera when we use the fitting voice commands. Various users in a family can get access to the virtual Assistant by facial recognition module.

Sign in / Sign up

Export Citation Format

Share Document