| Proj No. | B3001-251 |
| Title | Deep learning technique for reducing ground penetrating radar measurements |
| 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 with the following responsibilities: - Developing a deep learning technique to interpolate the 2D GPR B-scans in 3D GPR C-Scans - Using this technique to complete the synthetic and measured GPR C-Scans The current study primarily involves software development, simulations, and measurements. |
| 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: | Digital Media Processing and Computer Engineering |
| ISP/RI/SMP/SCP?: | ISP: Dr James Wang Deputy Director (CUGE) NParks James_WANG@nparks.gov.sg |