Deep learning based estimation of wall parameters for through-the-wall imaging
This project explores the use of deep learning algorithms, particularly Convolutional Neural Networks (CNNs), to estimate wall parameters in Through-the-Wall Imaging (TWI). TWI utilizes Ground Penetrating Radar (GPR) to detect objects hidden behind walls, but distinguishing between the target and cl...
Saved in:
主要作者: | Joseph, Christian |
---|---|
其他作者: | Abdulkadir C. Yucel |
格式: | Final Year Project |
語言: | English |
出版: |
Nanyang Technological University
2024
|
主題: | |
在線閱讀: | https://hdl.handle.net/10356/181594 |
標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|
機構: | Nanyang Technological University |
語言: | English |
相似書籍
-
Simulation tools for through wall imaging
由: Cheng, Kaixuan
出版: (2021) -
Estimation of diaphragm wall deflections for deep braced excavation in anisotropic clays using ensemble learning
由: Zhang, Runhong, et al.
出版: (2021) -
Simulation studies on through-wall radar imaging
由: Tham, Wilson Wei Hsen
出版: (2011) -
Through-wall imaging: Application of subspace-based optimization method
由: Lu, T., et al.
出版: (2014) -
Effects of synthesis parameters on size of double-walled particles
由: Lim, Alvin Wei Yang.
出版: (2010)