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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محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Yeo, Joseph ChengJie
مؤلفون آخرون: Abdulkadir C. Yucel
التنسيق: Final Year Project
اللغة:English
منشور في: Nanyang Technological University 2023
الموضوعات:
الوصول للمادة أونلاين:https://hdl.handle.net/10356/167668
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المؤسسة: Nanyang Technological University
اللغة: English
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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
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