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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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2023
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| Online Access: | https://hdl.handle.net/10356/167668 |
| _version_ | 1826113393105305600 |
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| author | Yeo, Joseph ChengJie |
| author2 | Abdulkadir C. Yucel |
| author_facet | Abdulkadir C. Yucel Yeo, Joseph ChengJie |
| author_sort | Yeo, Joseph ChengJie |
| collection | NTU |
| 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. |
| first_indexed | 2024-10-01T03:22:29Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/167668 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T03:22:29Z |
| publishDate | 2023 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-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 |
| spellingShingle | Engineering::Electrical and electronic engineering Yeo, Joseph ChengJie Deep learning algorithm to generate real radar images |
| title | 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_short | Deep learning algorithm to generate real radar images |
| title_sort | deep learning algorithm to generate real radar images |
| topic | Engineering::Electrical and electronic engineering |
| url | https://hdl.handle.net/10356/167668 |
| work_keys_str_mv | AT yeojosephchengjie deeplearningalgorithmtogeneraterealradarimages |