Deep learning algorithms to image the tree interiors via scans on a straight trajectory

This project introduces a deep learning approach to reconstruct images of tree interiors via a straight trajectory scan. The radar captures signals reflected from the tree trunk while it moves along a linear path at a distance from the trunk's surface. These signals, represented as B-scans, are...

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Main Author: Bui, Quang Huy
Other Authors: Abdulkadir C. Yucel
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2024
Subjects:
Online Access:https://hdl.handle.net/10356/177081
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1770812024-05-31T15:42:49Z Deep learning algorithms to image the tree interiors via scans on a straight trajectory Bui, Quang Huy Abdulkadir C. Yucel Lee Yee Hui School of Electrical and Electronic Engineering National Parks Board (NParks) acyucel@ntu.edu.sg, EYHLee@ntu.edu.sg Computer and Information Science Earth and Environmental Sciences Engineering Deep learning Straight trajectory scans Tree interiors imaging Image-to-image translation Model optimization Dataset development This project introduces a deep learning approach to reconstruct images of tree interiors via a straight trajectory scan. The radar captures signals reflected from the tree trunk while it moves along a linear path at a distance from the trunk's surface. These signals, represented as B-scans, are processed, and employed as the datasets for a modified U-Net model, with the ground truth as tree cross sectional image. The goal of the project is to reconstruct the image of the tree cross sectional image to be as close as possible to the ground truth, so that it can be applied to detect trees that is on the verge of falling in real life, therefore avoiding accidents. After experimenting with different model training approaches, loss functions and hyperparameter combinations, a very high accuracy has been achieved in imaging the tree interiors. The project hence holds significant practical potential in the future. By providing accurate and efficient tree assessment method, the project can assist the authorities in creating effective forest management and conservation strategies, hence minimizing the overall number of tree fall accidents. Bachelor's degree 2024-05-26T23:38:11Z 2024-05-26T23:38:11Z 2024 Final Year Project (FYP) Bui, Q. H. (2024). Deep learning algorithms to image the tree interiors via scans on a straight trajectory. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/177081 https://hdl.handle.net/10356/177081 en B3004-231 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 Computer and Information Science
Earth and Environmental Sciences
Engineering
Deep learning
Straight trajectory scans
Tree interiors imaging
Image-to-image translation
Model optimization
Dataset development
spellingShingle Computer and Information Science
Earth and Environmental Sciences
Engineering
Deep learning
Straight trajectory scans
Tree interiors imaging
Image-to-image translation
Model optimization
Dataset development
Bui, Quang Huy
Deep learning algorithms to image the tree interiors via scans on a straight trajectory
description This project introduces a deep learning approach to reconstruct images of tree interiors via a straight trajectory scan. The radar captures signals reflected from the tree trunk while it moves along a linear path at a distance from the trunk's surface. These signals, represented as B-scans, are processed, and employed as the datasets for a modified U-Net model, with the ground truth as tree cross sectional image. The goal of the project is to reconstruct the image of the tree cross sectional image to be as close as possible to the ground truth, so that it can be applied to detect trees that is on the verge of falling in real life, therefore avoiding accidents. After experimenting with different model training approaches, loss functions and hyperparameter combinations, a very high accuracy has been achieved in imaging the tree interiors. The project hence holds significant practical potential in the future. By providing accurate and efficient tree assessment method, the project can assist the authorities in creating effective forest management and conservation strategies, hence minimizing the overall number of tree fall accidents.
author2 Abdulkadir C. Yucel
author_facet Abdulkadir C. Yucel
Bui, Quang Huy
format Final Year Project
author Bui, Quang Huy
author_sort Bui, Quang Huy
title Deep learning algorithms to image the tree interiors via scans on a straight trajectory
title_short Deep learning algorithms to image the tree interiors via scans on a straight trajectory
title_full Deep learning algorithms to image the tree interiors via scans on a straight trajectory
title_fullStr Deep learning algorithms to image the tree interiors via scans on a straight trajectory
title_full_unstemmed Deep learning algorithms to image the tree interiors via scans on a straight trajectory
title_sort deep learning algorithms to image the tree interiors via scans on a straight trajectory
publisher Nanyang Technological University
publishDate 2024
url https://hdl.handle.net/10356/177081
_version_ 1800916170782539776