scholarly journals A Study on the Laws Governing Facial Recognition Technology and Data Privacy in Malaysia

2021 ◽  
Vol 6 (10) ◽  
pp. 480-487
Author(s):  
Muhammad Ashraf Bin Mohd Nor ◽  
Mohammad Asyraf Bin Mohd Tasrib ◽  
Bryan Francis ◽  
Nurul Izzah Binti Hesham ◽  
Mohd Bahrin Bin Othman
Keyword(s):  
Data Collection ◽  
Data Privacy ◽  
Facial Recognition ◽  
Data Sets ◽  
The Past ◽  
Face Detection And Recognition ◽  
Complex Technology ◽  
Laws And Policies ◽  
Facial Images ◽  
Detection And Recognition

The advancement of technology in the past decade has led humans to achieve many great things. Among that is facial recognition technology that uses a combination of two techniques which is face detection and recognition that is capable of converting facial images of a person into readable data and connecting it with other data sets which enable it to identify, track or compare it. This study delves into the usage of facial recognition technology in Malaysia where its regulation is almost non-existent. As its usage increases, the invasive features of this technology to collect and connect its data posed a threat to the data privacy of Malaysian citizens. Due to this issue, other countries' laws and policies regarding this technology are examined and compared with Malaysia. This enables the loopholes of the current law and policies to be identified and restructured, which create a clear path on the proper regulations and changes that need to be made. Thus, this study aims to analyse the limitation of law governing data privacy and its concept in Malaysia along with changes that need to be made. This study’s finding shows the shortcoming of Malaysia’s law in governing data privacy especially when it involves complex technology that has great data collection capability like facial recognition.

scholarly journals A Dataset for Comparing Mirrored and Non-Mirrored Male Bust Images for Facial Recognition

Data ◽  
2019 ◽  
Vol 4 (1) ◽  
pp. 26 ◽  
Author(s):  
Collin Gros ◽  
Jeremy Straub
Keyword(s):  
Data Collection ◽  
Facial Recognition ◽  
Data Sets ◽  
Similar Data ◽  
Data Set ◽  
Human Recognition ◽  
Related Research

Facial recognition, as well as other types of human recognition, have found uses in identification, security, and learning about behavior, among other uses. Because of the high cost of data collection for training purposes, logistical challenges and other impediments, mirroring images has frequently been used to increase the size of data sets. However, while these larger data sets have shown to be beneficial, their comparative level of benefit to the data collection of similar data has not been assessed. This paper presented a data set collected and prepared for this and related research purposes. The data set included both non-occluded and occluded data for mirroring assessment.

Secure Building Blocks for Data Privacy

2011 ◽  
pp. 1741-1746
Author(s):  
Shuguo Han
Keyword(s):  
Data Mining ◽  
Data Collection ◽  
Data Storage ◽  
Data Privacy ◽  
Building Blocks ◽  
Modern World ◽  
Data Sets ◽  
Privacy Concerns ◽  
Data Mining Algorithms ◽  
Wide Availability

Rapid advances in automated data collection tools and data storage technology have led to the wide availability of huge amount of data. Data mining can extract useful and interesting rules or knowledge for decision making from large amount of data. In the modern world of business competition, collaboration between industries or companies is one form of alliance to maintain overall competitiveness. Two industries or companies may find that it is beneficial to collaborate in order to discover more useful and interesting patterns, rules or knowledge from their joint data collection, which they would not be able to derive otherwise. Due to privacy concerns, it is impossible for each party to share its own private data with one another if the data mining algorithms are not secure. Therefore, privacy-preserving data mining (PPDM) was proposed to resolve the data privacy concerns while yielding the utility of distributed data sets (Agrawal & Srikant, 2000; Lindell.Y. & Pinkas, 2000). Conventional PPDM makes use of Secure Multi-party Computation (Yao, 1986) or randomization techniques to allow the participating parties to preserve their data privacy during the mining process. It has been widely acknowledged that algorithms based on secure multi-party computation are able to achieve complete accuracy, albeit at the expense of efficiency.

scholarly journals REAL TIME FACE DETECTION AND RECOGNITION SYSTEM USING HAAR CASCADE CLASSIFIER AND NEURAL NETWORKS

2021 ◽  
Vol 9 (1) ◽  
pp. 224-231
Author(s):  
Anirban Chakraborty, Shilpa Sharma
Keyword(s):  
Face Detection ◽  
Facial Recognition ◽  
Recognition System ◽  
Recognition Algorithm ◽  
Smart Device ◽  
Cascade Classifier ◽  
Face Detection And Recognition ◽  
Haar Cascade ◽  
The Times ◽  
Detection And Recognition

Home protection and privacy have become one of the most critical aspects in today's world. As technology progresses at an exponential pace, the times are not far ahead for each house to be fitted with sophisticated security systems to deal with regular burglary and theft. But as one side of the tech progresses, so do its detrimental counterparts. DES encryption can be an indicator of how easily an encrypted piece of information can be deciphered. Not long after its release, DES encryption was referred to as 'unsafe' and with today's modern application, anything like DES might be an open invitation to hack. With many developments in the field, the technology has, in many respects, surpassed the use of biometrics (finger prints). Face recognition, nowadays, is present in almost every smart device that has some piece of information stored that holds importance to its users. With facial recognition gaining popularity, many tech companies have come with their own patent to make a technology related to Facial Recognition on the market. This paper suggests a somewhat related concept as to how home protection can be improved by using a face detection and recognition algorithm (Haar Cascade Classifier).

Comparison of Face Detection and Recognition Algorithms in Real-Time Video

2020 ◽  
Author(s):  
Alejandra Sarahi Sanchez-Moreno ◽  
Hector Manuel Perez-Meana ◽  
Jesus Olivares-Mercado ◽  
Gabriel Sanchez-Perez ◽  
Karina Toscano-Medina
Keyword(s):  
Real Time ◽  
Face Detection ◽  
High Performance ◽  
Facial Recognition ◽  
Rapid Development ◽  
Real Time Systems ◽  
The Face ◽  
Face Detection And Recognition ◽  
Time Systems ◽  
Detection And Recognition

Facial recognition systems has captivated research attention in recent years. Facial recognition technology is often required in real-time systems. With the rapid development, diverse algorithms of machine learning for detection and facial recognition have been proposed to address the challenges existing. In the present paper we proposed a system for facial detection and recognition under unconstrained conditions in video sequences. We analyze learning based and hand-crafted feature extraction approaches that have demonstrated high performance in task of facial recognition. In the proposed system, we compare different traditional algorithms with the avant-garde algorithms of facial recognition based on approaches discussed. The experiments on unconstrained datasets to study the face detection and face recognition show that learning based algorithms achieves a remarkable performance to face the challenges in real-time systems.

scholarly journals Real Time Implementation of Face Recognition based Smart Attendance System

2021 ◽  
Vol 17 ◽  
pp. 46-56
Author(s):  
Md. Salah Uddin Yusuf ◽  
Azmol Ahmed Fuad
Keyword(s):  
Real Time ◽  
Graphical User Interface ◽  
Facial Recognition ◽  
Research Work ◽  
Third Party ◽  
Computational Time ◽  
Resource Requirement ◽  
Proposed Model ◽  
Face Detection And Recognition ◽  
Detection And Recognition

This research work addresses the issue of incorporating an automatic attendance system to the frame of an institution using face detection and recognition techniques. The proposed system aims at reducing computational time with available hardware to yield more efficient results. The proposed model utilizes Histogram Oriented Gradients and facial encodings derived from facial landmarks. It also addresses the problems related to accuracy of facial recognition and the resource requirement for quick, real-time facial recognition by applying multi-processing. The improvement in performance in terms of accuracy across two different methods, and the improvement in terms of time requirement for the same method using different strategies have also been documented for demonstration. The designed system demonstrates the effectiveness of task parallelization with a minimum amount of hardware desiderata. The system has been designed to an optimum self-sustaining ecosystem which can efficiently operate on its own accord and compute comprehensible feedback without the requirement of any third-party human interference. A Graphical User Interface has been incorporated into the system for maximum user comprehensibility

The past, present and future of food consumption databases

2012 ◽  
Vol 153 (43) ◽  
pp. 1692-1700
Author(s):  
Viktória Szűcs ◽  
Erzsébet Szabó ◽  
Diána Bánáti
Keyword(s):  
Data Collection ◽  
Food Consumption ◽  
Age Groups ◽  
Collection Method ◽  
The Past ◽  
Consumption Data ◽  
Food Consumption Data ◽  
International Projects ◽  
Collection Methods ◽  
The Eu

Results of the food consumption surveys are utilized in many areas, such as for example risk assessment, cognition of consumer trends, health education and planning of prevention projects. Standardization of national consumption data for international comparison is an important task. The intention work began in the 1970s. Because of the widespread utilization of food consumption data, many international projects have been done with the aim of their harmonization. The present study shows data collection methods for groups of the food consumption data, their utilization, furthermore, the stations of the international harmonization works in details. The authors underline that for the application of the food consumption data on the international level, it is crucial to harmonize the surveys’ parameters (e.g. time of data collection, method, number of participants, number of the analysed days and the age groups). For this purpose the efforts of the EU menu project, started in 2012, are promising. Orv. Hetil., 2012, 153, 1692–1700.

Participant recruitment and data collection through Facebook: the role of personality factors

2017 ◽  
Author(s):  
Sean Chandler Rife ◽  
Kelly L. Cate ◽  
Michal Kosinski ◽  
David Stillwell
Keyword(s):  
Data Collection ◽  
Social Research ◽  
Personality Factors ◽  
The Internet ◽  
Data Sets ◽  
Social Networking Service ◽  
Participant Recruitment ◽  
Conducting Research ◽  
Promising Avenue

As participant recruitment and data collection over the Internet have become more common, numerous observers have expressed concern regarding the validity of research conducted in this fashion. One growing method of conducting research over the Internet involves recruiting participants and administering questionnaires over Facebook, the world’s largest social networking service. If Facebook is to be considered a viable platform for social research, it is necessary to demonstrate that Facebook users are sufficiently heterogeneous and that research conducted through Facebook is likely to produce results that can be generalized to a larger population. The present study examines these questions by comparing demographic and personality data collected over Facebook with data collected through a standalone website, and data collected from college undergraduates at two universities. Results indicate that statistically significant differences exist between Facebook data and the comparison data-sets, but since 80% of analyses exhibited partial η2 < .05, such differences are small or practically nonsignificant in magnitude. We conclude that Facebook is a viable research platform, and that recruiting Facebook users for research purposes is a promising avenue that offers numerous advantages over traditional samples.

Sicker and Poorer—The Consequences of Being Uninsured: A Review of the Research on the Relationship between Health Insurance, Medical Care Use, Health, Work, and Income

2003 ◽  
Vol 60 (2_suppl) ◽  
pp. 3S-75S ◽  
Author(s):  
Jack Hadley
Keyword(s):  
Health Insurance ◽  
Medical Care ◽  
Data Sets ◽  
Work Effort ◽  
Services Research ◽  
The Past ◽  
Medical Care Use ◽  
Process Studies ◽  
Annual Earnings ◽  
The Relationship

Health services research conducted over the past 25 years makes a compelling case that having health insurance or using more medical care would improve the health of the uninsured. The literature's broad range of conditions, populations, and methods makes it difficult to derive a precise quantitative estimate of the effect of having health insurance on the uninsured's health. Some mortality studies imply that a 4% to 5% reduction in the uninsured's mortality is a lower bound; other studies suggest that the reductions could be as high as 20% to 25%. Although all of the studies reviewed suffer from methodological flaws of varying degrees, there is substantial qualitative consistency across studies of different medical conditions conducted at different times and using different data sets and statistical methods. Corroborating process studies find that the uninsured receive fewer preventive and diagnostic services, tend to be more severely ill when diagnosed, and receive less therapeutic care. Other literature suggests that improving health status from fair or poor to very good or excellent would increase both work effort and annual earnings by approximately 15% to 20%.

Sign in / Sign up

Export Citation Format

Share Document