Lustre, Marc Vien L., author.
FRAMS : Face Recognition Attendance Management System of Cavite State University - CCAT / Marc Vien L. Lustre, Jazmin Shin D. Pangilinan, and Lucky B. Combinido. - Rosario, Cavite : Cavite State University-CCAT Campus, 2019. - xi, 60 leaves : illustrations ; 28 cm
An Undergraduate Thesis (BSCS) -- Cavite State University-CCAT Campus, 2019.
Includes bibliographical references and appendices.
LUSTRE, MARC VIEN L., PANGILINAN, JASMIN SHIN D., COMBINIDO, LUCKY B.FRAMS: Face Recognition Attendance Management System Using Image Processing for Cavite State University CCAT. Cavite State University - CCAT, Rosario, Cavite. May 2019. Adviser: Prof. Christopher G. Estonilo.
The study was conducted from August 2018 to April 2019 to improve the class monitoring system using FRAMS or Face Recognition Attendance Management System The general objective of the study was to improve the class attendance monitoring system in Cavite State University - CCAT Specifically, the study aimed to: 1) design and develop the class attendance monitoring system in Cavite State University- CCAT, which is capable of entering the class information of the instructor, scanning. training and testing the face of students belong to the class, recognizing the face of students presents in the class, and providing reports of class attendance, 2) evaluate the system using ISO-IE 25010 software evaluation standards, and3) prepare an implementation plan for the deployment of the system in the Department of Computer Studies
The system analysis and design of FRAMS applied the rapid application development or RAD software development model which was composed of requirement analysis, user design (prototype, test, refine), construction, and cut over
The mobile application was evaluated by five (5) IT experts and (15) general end- user in the campus It gained a mean of 4.52 and described as Excellent for the IT experts. On the other hand, it gained a mean of 4.6 and also described as Excellent for the end-users.
In English text.
Face recognition.
Image processing.
Computer vision.
Human face recognition ( Computer Science ).
Biometric identification.
Attendance Management System.
UM TA 1650 / L87 2019
FRAMS : Face Recognition Attendance Management System of Cavite State University - CCAT / Marc Vien L. Lustre, Jazmin Shin D. Pangilinan, and Lucky B. Combinido. - Rosario, Cavite : Cavite State University-CCAT Campus, 2019. - xi, 60 leaves : illustrations ; 28 cm
An Undergraduate Thesis (BSCS) -- Cavite State University-CCAT Campus, 2019.
Includes bibliographical references and appendices.
LUSTRE, MARC VIEN L., PANGILINAN, JASMIN SHIN D., COMBINIDO, LUCKY B.FRAMS: Face Recognition Attendance Management System Using Image Processing for Cavite State University CCAT. Cavite State University - CCAT, Rosario, Cavite. May 2019. Adviser: Prof. Christopher G. Estonilo.
The study was conducted from August 2018 to April 2019 to improve the class monitoring system using FRAMS or Face Recognition Attendance Management System The general objective of the study was to improve the class attendance monitoring system in Cavite State University - CCAT Specifically, the study aimed to: 1) design and develop the class attendance monitoring system in Cavite State University- CCAT, which is capable of entering the class information of the instructor, scanning. training and testing the face of students belong to the class, recognizing the face of students presents in the class, and providing reports of class attendance, 2) evaluate the system using ISO-IE 25010 software evaluation standards, and3) prepare an implementation plan for the deployment of the system in the Department of Computer Studies
The system analysis and design of FRAMS applied the rapid application development or RAD software development model which was composed of requirement analysis, user design (prototype, test, refine), construction, and cut over
The mobile application was evaluated by five (5) IT experts and (15) general end- user in the campus It gained a mean of 4.52 and described as Excellent for the IT experts. On the other hand, it gained a mean of 4.6 and also described as Excellent for the end-users.
In English text.
Face recognition.
Image processing.
Computer vision.
Human face recognition ( Computer Science ).
Biometric identification.
Attendance Management System.
UM TA 1650 / L87 2019