Query: attendance monitoring system for employee using face recognition

title: Automated Attendance Monitoring System using Facial Recognition
abstract: Attendance recording is one of the most imperative task of each and every institute. There are several traditional methods proposed for the same but each method is having its own drawbacks and also they are time consuming. For example, manually recorded attendance can be easily manipulated and also it is monotonous. So there is a need of a method that can overcome all drawbacks of traditional approach and can mark the attendance more efficiently. This paper presents a method in which attendance will be marked using the facial recognition of the person. Human face can be used to mark the attendance of the student employee and can play a vital role for the verification purpose and can also avoid proxies. This paper aims to provide a digitized way for attendance marking.

title: Hybrid Computerized Face Recognition System Using Bag of Visual Words and MLP Based BPNN
abstract: Nowadays in a situation like the Covid19 pandemic it is very sensitive to use biometric systems for attendance monitoring of employees. The reason is covid19 spreads from one person to another easily with a biometric system. It has become necessary for any organization to maintain an attendance monitoring system without taking fingerprints of any employee or a student. The automatic Face recognition system is best to alternate for the biometric system. An advanced automatic face recognition technique is proposed in this paper with the classification technique using Bag of Visual Words (BOVW) and Multi Layer Perceptron (MLP) based Back Propagation Neural Network (BPNN) An Accuracy of 91% is achieved with the proposed methodology.

title: Perancangan Absensi Berbasis Face Recognition Pada
abstract: The development of technology is currently very fast in various fields of human life. One of the uses of technology is in the field of attendance. Attendance is the most important part in an institution, both education, health, offices and government agencies in supporting monitoring of employees' daily attendance.Sokaraja Lor Village is a village located in Sokaraja District, Kab. Banyumas, Central Java.Currently the attendance process at the Sokaraja Lor village office is still using Pinjer Print and also using notes using a ledger.The use of this print pin is considered ineffective because if the village employee's hands are wet, or injured, attendance cannot be done and this is also a risk that village employees can leave absences to other employees.Seeing this, the researchers designed an attendance system based on Face Recognition using the Android platform. Face recognition based attendance is attendance 92 Jatisi ISSN 2407 4322 Vol. 8, No. 1, Maret 2021, Hal. 91 104 E ISSN 2503 2933 Darmansah, et.,al (Perancangan Absensi Berbasis Face Recognition Pada Desa Sokaraja Lor Menggunakan Platform Android) which is done using the detection of human face parts.Then in designing the face recognitionbased attendance system, the researchers used a system modeling with Undifinied Modeling Language (UML).With the construction of this attendance system, Sokaraja Lor Village can make attendance easier in every condition because it is based on Android, then in recapitulating the list of employees who are present, the village government is easier because it has been stored in a database.  Perancangan, Absensi, Face Recognition, UML, Android

title: PRESENT: An Android Based Class Attendance Monitoring System Using Face Recognition Technology
abstract: The study aimed to develop an Android Based Class Attendance Monitoring Application using Face Recognition to make attendance checking and monitoring easier and faster. In addition, the system has also integrated the use of SMS technology to notify parents/guardians whenever the students attended a particular subject or class. In addition, the study also intended to evaluate the developed application in terms of functionality, usability, reliability, and portability.  The researcher utilized the incremental model. After the development phase, the application was evaluated by seventeen (17) faculty members from the College of Engineering and Computing Sciences. A validated evaluation questionnaire was used to rate the level of acceptability of the application based on ISO 9126 software quality and the level of satisfaction for its major features. For the statistical treatment of the data collected, Likert Scale, weighted mean and t test were utilized by the researcher.  The results revealed that instructors find the existing way of checking attendance as time consuming and a tedious task. Furthermore, the respondents assessed the developed application as moderately acceptable in terms of functionality, reliability and usability while portability was rated as highly acceptable. With regards to the features, the respondents were very satisfied. The t test also revealed that there is a significant difference between the level respondents' level of acceptability on the existing and the proposed system.  The researcher concluded that the developed application was useful and it can support the needs of the instructors to make attendance checking and monitoring easier, faster, and reliable. Recommendations Due to its acceptable evaluation result, instructors should consider the use of this tool as an alternative to the existing process of checking and monitoring class attendance. The developed system can be enhanced in terms of user design to make it more user friendly.  Classroom presence is important because this helps students to succeed in their academics when they attend class regularly. With the integration of different technologies such as Android, face recognition and SMS, the traditional way of checking class attendance can be made easier, faster, reliable and secured, thus improving classroom management.

title: Smart Group Attendance Monitoring System using Face Recognition

title: Vision Face Recognition Attendance Monitoring System for Surveillance using Deep Learning Technology and Computer Vision
abstract: Nowadays, Artificial Neural networks can be trained over several billion images and can be used to detect and recognize faces with relative ease and flexibility in an instant. This concept is used in the implementation of this real time attendance cum surveillance system that can be prototyped and set into action. Some of the major applications of this innovative method include face attendance using a single snap mode in smartphones for university classes, further real time facial recognition surveillance of lab facilities and work places which can set this as a first line of defense against intruders from gaining access. The user friendly graphical user interface provides flexibility and ease in running these powerful face recognition algorithms powered by deep learning. We have achieved a maximum recognition accuracy of 74 percent while running the real time surveillance algorithm. This work was done as a solution to the absence of a robust and user friendly face recognition attendance system.

title: Automated Face Recognition for Student Attendance Monitoring System Using PCA Algorithm
abstract: Human face recognition and detection is a very important technology within the biometric verification and it's been utilized in numerous applications like interaction with human computer and security, video monitor system. This paper primarily describes concerning the group action for college kids. for each library, faculties and schools group action is needed. Historical methodology for taking group action is lecturer occupation name of a student and capture the group action in a very sheet. It's a time waste method. it's a tedious task to proof entire student's gift in a very schoolroom. to stay away these losses, we tend to use automatic group action system. The designed system describes a way like once he\she enters the category area and it blots the group action by uprooting the image mistreatment PCA (Principal component Analysis) rule. This method can document the group action of the coed at school area setting mechanically. the coed information is collected. The coed information contains students name, photos their roll numbers. it stores a additional introduction every student with value more highly to each course and additionally initiate a detail of every student group action. Mistreatment SMTP protocol, the category group action information is sent to folks and similarly as college

title: Face Recognition Based Attendance Monitoring System using Raspberry pi and OpenCV
abstract: 1,2BE Scholar, Department of Electronics and telecommunication, PCET's Pimpri Chinchwad college of Engineering, MH, India Abstract Recently face recognition is attracting much attention in the society of network multimedia information access. Areas such as network security, content indexing and retrieval, and video compression benefits from face recognition technology because "people" are the center of attention in a lot of video. Face recognition is the identification of humans by the unique characteristics of their Faces. Face recognition technology is the least intrusive and fastest biometric technology. It works with the most obvious individual identifier the human face. This system aims at providing a system to automatically record the students' attendance during lecture hours in a hall or room using raspberry pi with the help of facial recognition technology instead of the traditional manual methods.

title: Face Recognition Application Using the Eigenface Method for Employee Attendance at STMIK Budi Darma
abstract: Attendance is one of the most important repetitive transactions because it is related to the productivity of employees and employees and is one of the controlling indicators Human resources (HR) which aim to increase the potential of human resources as well used in the framework of efficiency. Current technological developments allow making a system that can assist humans in recognizing a digital image. One of them, a field that is currently being developed is pattern recognition. This technology identifies the special physical characteristics of a person. An example of pattern recognition is an example of face recognition, iris recognition, fingerprint recognition (finger recognition) and others. The face is part of the human body to be the focus of attention in social interactions. The face has a very important role that can show someone's identity; therefore a face can be used as a part of the human body that is used as an indication of knowing someone or face recognition. Attendance is an administrative act regarding attendance and absence attendance of employees. In this facial recognition, research uses a camera to capturing someone's face was then compared to the face that had previously been stored in a specific database. Broadly speaking, the process of facial recognition is the webcam camera captures the face. Then we get an R (read) value, G (Green) B (Blue) Using pre processing, cropped, RGB to grayscale. After the Grayscale process is carried out, the face processing stage is carried out using the eigenface method. In this eigenface method, there are several core stages namely: converting faces to matrices, calculating Flat Vector averages, determining values eigenface, and perform the face identification process by looking for the eigenface value approaching. One of the ways of facial recognition can be developed into an application absence that can be applied in companies to prevent manipulation of absences by employees or employees.

title: Attendance Monitoring System Using Face Recognition
abstract: Initially the database which contains the images of all the student's will be created. The model is fixed in the class in such a way that all the student's faces are captured clearly. Once the teacher enters/finishes the class then they have to login to the model then the camera will take the picture of whole class. Then image will be cropped into individual student and cropped image will be updated on the main server automatically. So that every student has the clarity of their attendance. In other words there is a transparency between student and teacher about attendance. Including to this, model also provide several features such as Automatic attendance percentage calculation and if a student absent for one class automatic message will be sent to the respective proctors and if a student absent for consecutive three classes automatic message will send to the respective proctors as well as parents. Status of attendance will be sent to the parents as well as students for every month. This system is more secure than the existing system and also requires less time to take the attendance.