MARC details
| 000 -LEADER |
| fixed length control field |
02506ntm a2200277 i 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
| control field |
OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
| control field |
20231021150022.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
| fixed length control field |
230823s2022 |||a|||| bm|| 00| 0 eng d |
| 040 ## - CATALOGING SOURCE |
| Original cataloging agency |
TUPM |
| Language of cataloging |
eng |
| Transcribing agency |
TUPM |
| Description conventions |
rda |
| 050 ## - LIBRARY OF CONGRESS CALL NUMBER |
| Classification number |
BTH QA 76 |
| Item number |
D45 2022 |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
| Personal name |
De Leon, Christian Noel U. |
| 245 10 - TITLE STATEMENT |
| Title |
Development of a Real-Time Facemask Detector Using YOLOv4 Object Detection Model and OpenCV / |
| Statement of responsibility, etc. |
Christian Noel U. De Leon, Ronald Andrie G. Mutuc, Jomari L. Tagra. |
| 264 ## - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
| Place of production, publication, distribution, manufacture |
Manila : |
| Name of producer, publisher, distributor, manufacturer |
Technological University of the Philippines, |
| Date of production, publication, distribution, manufacture, or copyright notice |
2022. |
| 300 ## - PHYSICAL DESCRIPTION |
| Extent |
x, 100 pages : |
| Other physical details |
illustrations ; |
| Dimensions |
28 cm. + |
| Accompanying material |
1 CD-ROM (4 3/4 in.) |
| 336 ## - CONTENT TYPE |
| Source |
rdacontent |
| Content type term |
text |
| 337 ## - MEDIA TYPE |
| Source |
rdamedia |
| Media type term |
unmediated |
| 338 ## - CARRIER TYPE |
| Source |
rdacarrier |
| Carrier type term |
volume |
| 500 ## - GENERAL NOTE |
| General note |
Thesis (Undergraduate) |
| 502 ## - DISSERTATION NOTE |
| Dissertation note |
College of Science -- |
| Degree type |
Bachelor of Science in Computer Science, |
| Name of granting institution |
Technological University of the Philippines, |
| Year degree granted |
2022. |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
| Bibliography, etc. note |
Includes bibliographical references. |
| 520 3# - SUMMARY, ETC. |
| Summary, etc. |
COVID-19 began more than 2 years ago and is still a threat to human lives today. One of the most important preventive measures that is still being implemented today is the wearing of facemasks. The general objective of the study is geared towards the development of real-time facemask detector entitled "Real-time Facemask Detector Using YOLOv4 Object Detection Model and OpenCV". The real-time facemask detector model was built using predefined weights of YOLOv4 and uncompressed version of CSPDarknet-53 with 53 convolutional layers serving as a backbone. The model will recognize whether the subject is wearing a facemask, incorrectly wearing one, or none at all. The model also used 856 images per class for training. Throughout the project development, the researchers followed the Agile methodology. While in testing, Portability and Reliability testing was performed then evaluated by different people from all age group. The result showed that the software can detect a 416x416 frame with a mean average precision of 94.60% in a class containing Correct facemasks, 60.47% in Incorrect, and 85.10% in no facemask. Furthermore, the system got an overall mean of 3.59 or "Highly Acceptable" rating from the thirty (30) respondents. The developed system is meant to provide aid to frontline workers who are in patrol implementing the basic health protocols.--Author's Abstract |
| 653 ## - INDEX TERM--UNCONTROLLED |
| Uncontrolled term |
Facemasks -- Detection. |
| -- |
Facemasks -- Recognition. |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
| Personal name |
Mutuc, Ronald Andrie G. |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
| Personal name |
Tagra, Jomari L. |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
| Source of classification or shelving scheme |
Library of Congress Classification |
| Koha item type |
Bachelor's Thesis COS |
| Suppress in OPAC |
No |