Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/153127
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dc.contributor.authorYang, Zhenen_US
dc.date.accessioned2021-11-08T01:10:27Z-
dc.date.available2021-11-08T01:10:27Z-
dc.date.issued2021-
dc.identifier.citationYang, 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/10356/153127en_US
dc.identifier.urihttps://hdl.handle.net/10356/153127-
dc.description.abstractThis 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.en_US
dc.language.isoenen_US
dc.publisherNanyang Technological Universityen_US
dc.subjectEngineering::Computer science and engineering::Computing methodologies::Image processing and computer visionen_US
dc.subjectEngineering::Computer science and engineering::Computing methodologies::Artificial intelligenceen_US
dc.titleEvaluations of deep learning methods for detection of gap in concrete structuresen_US
dc.typeThesis-Master by Courseworken_US
dc.contributor.supervisorCheah Chien Chernen_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeMaster of Science (Computer Control and Automation)en_US
dc.contributor.supervisoremailECCCheah@ntu.edu.sgen_US
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