000 03069nam a22003377a 4500
003 OSt
005 20240506054918.0
008 240501b ||||| |||| 00| 0 eng d
040 _bEnglish.
_cCvSU-CCAT Campus Library.
_erda.
050 _aUM TA 1650
_bL87 2019
100 _aLustre, Marc Vien L., author.
_911832
245 _aFRAMS : Face Recognition Attendance Management System of Cavite State University - CCAT /
_cMarc Vien L. Lustre, Jazmin Shin D. Pangilinan, and Lucky B. Combinido.
260 _aRosario, Cavite :
_bCavite State University-CCAT Campus,
_c2019.
300 _axi, 60 leaves :
_billustrations ;
_c28 cm
500 _aAn Undergraduate Thesis (BSCS) -- Cavite State University-CCAT Campus, 2019.
504 _aIncludes bibliographical references and appendices.
520 _aLUSTRE, 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.
546 _aIn English text.
650 _aFace recognition.
_911833
650 _aImage processing.
_95797
650 _aComputer vision.
_95544
650 _aHuman face recognition ( Computer Science ).
_911834
650 _aBiometric identification.
_95535
650 _aAttendance Management System.
_911835
700 _aPangilinan, Jasmin Shin D., author.
_911836
700 _aCombinido, Lucky B., author.
_911837
700 _aEstonilo, Christopher G., adviser.
_95822
700 _aRamos, Dann Patrick G., technical critic.
_911806
942 _2lcc
_cT/M/D
_hTA 1650 L87 2019
_kUM
999 _c3245
_d3245