Deep learning and image processing algorithms for tree defect detection
This paper is the final report for the final year project titled ‘Deep Learning and Image Processing Algorithms for Tree Defect Detection’. The main purpose of this report is to document all the experiments that was conducted throughout the whole project progress. The results that were obtained will...
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Nanyang Technological University
2022
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sg-ntu-dr.10356-1581322023-07-07T19:12:26Z Deep learning and image processing algorithms for tree defect detection Tan, Jun Zuo Abdulkadir C. Yucel Lee Yee Hui School of Electrical and Electronic Engineering NParks acyucel@ntu.edu.sg, EYHLee@ntu.edu.sg Engineering::Electrical and electronic engineering This paper is the final report for the final year project titled ‘Deep Learning and Image Processing Algorithms for Tree Defect Detection’. The main purpose of this report is to document all the experiments that was conducted throughout the whole project progress. The results that were obtained will also be documented down in this report. This report is 33 pages long excluding the cover page, abstract, content page, reference, and appendix. The main aim of this project is to produce an algorithm that will speed up the detection of defective trees, so as to minimize the possible casualties from trees falling. Bachelor of Engineering (Electrical and Electronic Engineering) 2022-05-30T12:13:05Z 2022-05-30T12:13:05Z 2022 Final Year Project (FYP) Tan, J. Z. (2022). Deep learning and image processing algorithms for tree defect detection. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/158132 https://hdl.handle.net/10356/158132 en B3004-211 application/pdf Nanyang Technological University |
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Engineering::Electrical and electronic engineering Tan, Jun Zuo Deep learning and image processing algorithms for tree defect detection |
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This paper is the final report for the final year project titled ‘Deep Learning and Image Processing Algorithms for Tree Defect Detection’. The main purpose of this report is to document all the experiments that was conducted throughout the whole project progress. The results that were obtained will also be documented down in this report. This report is 33 pages long excluding the cover page, abstract, content page, reference, and appendix.
The main aim of this project is to produce an algorithm that will speed up the detection of defective trees, so as to minimize the possible casualties from trees falling. |
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Abdulkadir C. Yucel |
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Abdulkadir C. Yucel Tan, Jun Zuo |
format |
Final Year Project |
author |
Tan, Jun Zuo |
author_sort |
Tan, Jun Zuo |
title |
Deep learning and image processing algorithms for tree defect detection |
title_short |
Deep learning and image processing algorithms for tree defect detection |
title_full |
Deep learning and image processing algorithms for tree defect detection |
title_fullStr |
Deep learning and image processing algorithms for tree defect detection |
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Deep learning and image processing algorithms for tree defect detection |
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deep learning and image processing algorithms for tree defect detection |
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Nanyang Technological University |
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2022 |
url |
https://hdl.handle.net/10356/158132 |
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1772825842645204992 |