Evaluations of deep learning methods for detection of gap in concrete structures
This dissertation applies 3 networks(FRCNN,Yolov3,Yolov4) to solve gap detection on a very small data set and make brief evaluations about their structures and performances.
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| 格式: | Thesis-Master by Coursework |
| 語言: | English |
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Nanyang Technological University
2021
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| 在線閱讀: | https://hdl.handle.net/10356/153127 |
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sg-ntu-dr.10356-1531272023-07-04T17:39:56Z Evaluations of deep learning methods for detection of gap in concrete structures Yang, Zhen Cheah Chien Chern School of Electrical and Electronic Engineering ECCCheah@ntu.edu.sg Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence This dissertation applies 3 networks(FRCNN,Yolov3,Yolov4) to solve gap detection on a very small data set and make brief evaluations about their structures and performances. Master of Science (Computer Control and Automation) 2021-11-08T01:10:27Z 2021-11-08T01:10:27Z 2021 Thesis-Master by Coursework Yang, Z. (2021). Evaluations of deep learning methods for detection of gap in concrete structures. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/153127 https://hdl.handle.net/10356/153127 en application/pdf Nanyang Technological University |
| institution |
Nanyang Technological University |
| building |
NTU Library |
| continent |
Asia |
| country |
Singapore Singapore |
| content_provider |
NTU Library |
| collection |
DR-NTU |
| language |
English |
| topic |
Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence |
| spellingShingle |
Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Yang, Zhen Evaluations of deep learning methods for detection of gap in concrete structures |
| description |
This dissertation applies 3 networks(FRCNN,Yolov3,Yolov4) to solve gap detection on a very small data set and make brief evaluations about their structures and performances. |
| author2 |
Cheah Chien Chern |
| author_facet |
Cheah Chien Chern Yang, Zhen |
| format |
Thesis-Master by Coursework |
| author |
Yang, Zhen |
| author_sort |
Yang, Zhen |
| title |
Evaluations of deep learning methods for detection of gap in concrete structures |
| title_short |
Evaluations of deep learning methods for detection of gap in concrete structures |
| title_full |
Evaluations of deep learning methods for detection of gap in concrete structures |
| title_fullStr |
Evaluations of deep learning methods for detection of gap in concrete structures |
| title_full_unstemmed |
Evaluations of deep learning methods for detection of gap in concrete structures |
| title_sort |
evaluations of deep learning methods for detection of gap in concrete structures |
| publisher |
Nanyang Technological University |
| publishDate |
2021 |
| url |
https://hdl.handle.net/10356/153127 |
| _version_ |
1772827788561088512 |