| Proj No. | B3004-251 |
| Title | Deep learning-based detection of tree roots in confined soil environments |
| Summary | Ground Penetrating Radar (GPR) is a crucial non-invasive tool for imaging tree roots. It is particularly important for detecting rotten roots and assessing the structural stability of trees. By providing real-time and high-resolution subsurface imagery, GPR enhances the assessment of tree health and helps prevent potential hazards and fatal tree fall accidents caused by weakened root systems. In this project, the student will help the research team by implementing AI algorithms for our ultra-wideband GPR with the following responsibilities: - Developing a semi-supervised learning algorithm-based denoiser and a supervised learning algorithm-based imager - Combining these algorithms to detect roots of trees in confined areas, such as the roots of trees in skyscrapers - Development of the database for machine learning algorithms via measurements The current study primarily involves software development and measurement campaigns. |
| Supervisor | Ast/P Abdulkadir C. Yucel (Loc:S2 > S2 B2C > S2 B2C 110, Ext: +65 67905403) |
| Co-Supervisor | Prof Lee Yee Hui (Loc:S2 > S2 B2C > S2 B2C 81, Ext: +65 67906188) |
| RI Co-Supervisor | - |
| Lab | Centre for Information Sciences & System (CISS) (Loc: S2-B4b-05) |
| Single/Group: | Single |
| Area: | Wireless and Communications Engineering |
| ISP/RI/SMP/SCP?: | ISP: Dr James Wang Deputy Director (CUGE) NParks James_WANG@nparks.gov.sg |