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