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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Bibliographic Details
Main Author:	Yang, Zhen
Other Authors:	Cheah Chien Chern
Format:	Thesis-Master by Coursework
Language:	English
Published:	Nanyang Technological University 2021
Subjects:	Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Online Access:	https://hdl.handle.net/10356/153127
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Institution:	Nanyang Technological University
Language:	English

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spelling	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

Evaluations of deep learning methods for detection of gap in concrete structures

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