| 000 -LEADER |
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02184nam a22002417a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
FT8838 |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20251128103750.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
251128b ||||| |||| 00| 0 eng d |
| 041 ## - LANGUAGE CODE |
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| Language code of text/sound track or separate title |
engtag |
| 050 ## - LIBRARY OF CONGRESS CALL NUMBER |
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| Classification number |
T58.64 F73 2025 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
. |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Francisco, Andrea Elaine; Jumanoy, Jowan Gavriel J.; Lim, Bryle Elys N. |
| 245 ## - TITLE STATEMENT |
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| Title |
iSukat: Capture, measure, and know your perfect shoe size using image recognition |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
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| Place of production, publication, distribution, manufacture |
. |
| Name of producer, publisher, distributor, manufacturer |
. |
| Date of production, publication, distribution, manufacture, or copyright notice |
c2025 |
| 300 ## - PHYSICAL DESCRIPTION |
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| Other physical details |
Capstone Project: (Bachelor of Science in Information Technology) - Pamantasan ng Lungsod ng Maynila, 2025 |
| 336 ## - CONTENT TYPE |
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| Source |
text |
| Content type term |
text |
| Content type code |
text |
| 337 ## - MEDIA TYPE |
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unmediated |
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unmediated |
| Media type code |
unmediated |
| 338 ## - CARRIER TYPE |
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volume |
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volume |
| Carrier type code |
volume |
| 505 ## - FORMATTED CONTENTS NOTE |
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| Formatted contents note |
<br/>ABSTRACT: Improper shoe sizing remains a widespread issue in online footwear shopping, with studies indicating that approximately 63-72% of consumers wear incorrectly sized shoes. This often leads to discomfort, dissatisfaction, and potential long-term foot health problems. In response, iSUKAT presents a web-based application that harnesses advanced image recognition and machine learning technologies to deliver accurate foot measurements and improve shoe selection for users. By utilizing Roboflow 3.0 with COCO-seg instance segmentation, the system processes foot images to extract precise dimensions, identify foot types such as Egyptian, Roman, and Germanic, and recognize shoe brands through visual pattern detection. The study addresses key challenges in digital shoe fitting, aiming to minimize sizing errors and enhance user satisfaction through automated, intelligent recommendations. The system supports seamless performance across devices, offering a user-friendly interface and real-time processing to ensure smooth operation. Evaluation using machine learning metrics such as mean average precision, segmentation accuracy, and inference time confirmed the model’s efficiency. Despite some concerns-where only 11.6% of users strongly agreed with the measurement accuracy while 40.6% raised issues----ISUKAT will demonstrated consistent performance in detection and recommendation. |
| 526 ## - STUDY PROGRAM INFORMATION NOTE |
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| Classification |
Filipiniana |
| 655 ## - INDEX TERM--GENRE/FORM |
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| Genre/form data or focus term |
academic writing |
| 942 ## - ADDED ENTRY ELEMENTS |
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| Source of classification or shelving scheme |
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| Item type |
Thesis/Dissertation |