Deep learning algorithm to generate real radar images

This report discusses a novel way to generate GPR straight scans using generative adversarial networks (GANs). Two pix2pix GANs were developed to generate simulated B-scans from 2D trunk images and realistic B-scans from simulated B-scans. Simulated B-scans were obtained through gprMax models and...

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Bibliographic Details
Main Author:	Yeo, Joseph ChengJie
Other Authors:	Abdulkadir C. Yucel
Format:	Final Year Project
Language:	English
Published:	Nanyang Technological University 2023
Subjects:	Engineering::Electrical and electronic engineering
Online Access:	https://hdl.handle.net/10356/167668
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Institution:	Nanyang Technological University
Language:	English

id	sg-ntu-dr.10356-167668
record_format	dspace
spelling	sg-ntu-dr.10356-1676682023-07-07T15:53:57Z Deep learning algorithm to generate real radar images Yeo, Joseph ChengJie Abdulkadir C. Yucel School of Electrical and Electronic Engineering acyucel@ntu.edu.sg Engineering::Electrical and electronic engineering This report discusses a novel way to generate GPR straight scans using generative adversarial networks (GANs). Two pix2pix GANs were developed to generate simulated B-scans from 2D trunk images and realistic B-scans from simulated B-scans. Simulated B-scans were obtained through gprMax models and real B-scans were obtained from measurement campaigns on real trunks. This method was shown to produce realistic images, similar to that of simulated and real measurements. Bachelor of Engineering (Electrical and Electronic Engineering) 2023-05-30T06:18:40Z 2023-05-30T06:18:40Z 2023 Final Year Project (FYP) Yeo, J. C. (2023). Deep learning algorithm to generate real radar images. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/167668 https://hdl.handle.net/10356/167668 en B3032-221 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::Electrical and electronic engineering
spellingShingle	Engineering::Electrical and electronic engineering Yeo, Joseph ChengJie Deep learning algorithm to generate real radar images
description	This report discusses a novel way to generate GPR straight scans using generative adversarial networks (GANs). Two pix2pix GANs were developed to generate simulated B-scans from 2D trunk images and realistic B-scans from simulated B-scans. Simulated B-scans were obtained through gprMax models and real B-scans were obtained from measurement campaigns on real trunks. This method was shown to produce realistic images, similar to that of simulated and real measurements.
author2	Abdulkadir C. Yucel
author_facet	Abdulkadir C. Yucel Yeo, Joseph ChengJie
format	Final Year Project
author	Yeo, Joseph ChengJie
author_sort	Yeo, Joseph ChengJie
title	Deep learning algorithm to generate real radar images
title_short	Deep learning algorithm to generate real radar images
title_full	Deep learning algorithm to generate real radar images
title_fullStr	Deep learning algorithm to generate real radar images
title_full_unstemmed	Deep learning algorithm to generate real radar images
title_sort	deep learning algorithm to generate real radar images
publisher	Nanyang Technological University
publishDate	2023
url	https://hdl.handle.net/10356/167668
_version_	1772825768390295552

Deep learning algorithm to generate real radar images

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