Deep learning algorithm for tree defect characterization
This study explores the potential of using Deep Learning (DL) to develop a non-invasive method for assessing the health of trees, with a focus on characterizing defects in tree trunks and estimating their size using Ground Penetrating Radar (GPR) images. The aim is to reduce the number of treefall i...
Saved in:
Main Author: | Grandhi, Dhanush Chandra Krishna Sai |
---|---|
Other Authors: | Abdulkadir C. Yucel |
Format: | Final Year Project |
Language: | English |
Published: |
Nanyang Technological University
2023
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/167679 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Deep learning algorithm for tree defect detection
by: Leow, Yi En
Published: (2022) -
Deep learning and image processing algorithms for tree defect detection
by: Tan, Jun Zuo
Published: (2022) -
Radar development for tree defect detection
by: Choo, Yida
Published: (2022) -
Tree defect detection via radar measurements
by: Tan, Jun Wei
Published: (2022) -
Deep learning algorithm to generate real radar images
by: Yeo, Joseph ChengJie
Published: (2023)