Deep learning based road damage detection and classification for Philippine road pavements (Record no. 28078)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 02319nam a22002537a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20231021150021.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 230822b |||||||| |||| 00| 0 eng d |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | TUPM |
| Language of cataloging | eng |
| Transcribing agency | - |
| Description conventions | rda |
| 050 ## - LIBRARY OF CONGRESS CALL NUMBER | |
| Classification number | DIS Q 325.73 |
| Item number | R49 2022 |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Reyes, Ryan C. |
| 245 ## - TITLE STATEMENT | |
| Title | Deep learning based road damage detection and classification for Philippine road pavements |
| Remainder of title | Ryan C. Reyes |
| 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 | 143 pages: |
| Other physical details | color illustration; |
| Dimensions | 28cm. |
| Accompanying material | +1 CD-ROM (4 3/4 in.) |
| 500 ## - GENERAL NOTE | |
| General note | Dissertation |
| 502 ## - DISSERTATION NOTE | |
| Dissertation note | College of Industrial Education-- |
| Degree type | Doctor of Technology. |
| Name of granting institution | Technological University of the Philippines. |
| Year degree granted | 2022 |
| 520 3# - SUMMARY, ETC. | |
| Summary, etc. | This Paper presents a YOLO based road damage detection and classification model that employs transfer learning approach where a pre-trained YOLOv7 model was trained for custom Philippine road damage datasets which are collections of 8004 images of Philippine road pavement containing instances of different road damages. in this supervised learning project, the bulk collection of images was labeled by the road experts for annotation using the on-line computer vision annotation tool (CVAT by Intel) to highlight the part of the images that contains the damage features fed in the learning training algorithm. the model development process begins with experimentations using initial datasets to determine the best model for the desk and proceeded with the final system of DL classifiers to predict the damage type of an input image. Experimentation verified the dominance of YOLOv7 which outperformed two other candidate YOLO variants for the task in terms of mean average precision and F1 score using initial datasets in the early stage of this study. the model was retrained with bigger datasets and produced a more competitive detection performance. the study also explored two (2) methods for the detection of road damage severity levels using the same datasets distributed across all severity labeled by road experts resulting to a slight decrease in the mean average precision scores and F1 measures-Author's Abstract |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Deep learning (Machine) |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | YOLO |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Machine learning |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Machine vision |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Road damage detection |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | Library of Congress Classification |
| Koha item type | Dissertation |
| Suppress in OPAC | No |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Home library | Current library | Shelving location | Date acquired | Inventory number | Total checkouts | Full call number | Barcode | Date last seen | Price effective from | Koha item type | Public note |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Library of Congress Classification | TUP Manila Library | TUP Manila Library | Thesis Section-2nd floor | 08/22/2023 | DIS-2280 | DIS T 185 R49 2022 c.2 | DIS0002280 | 08/22/2023 | 08/22/2023 | Dissertation | For room use only | |||||
| Library of Congress Classification | TUP Manila Library | TUP Manila Library | Thesis Section-2nd floor | 08/22/2023 | DIS-2154 | DIS T 185 R49 2022 c.1 | DIS0002154 | 08/23/2023 | 08/22/2023 | Dissertation | For room use only |