| Proj No. | A1058-251 |
| Title | News Classification using Deep Learning Techniques |
| Summary | News classification is the automated categorization of news articles into predefined topics such as politics, sports, business, and entertainment. This project aims to develop a deep learning-based news classification system with the following objectives: (1) Design and implement deep neural network models for accurate news classification. (2) Optimize model performance using transfer learning and fine-tuning techniques. |
| Supervisor | A/P Mao Kezhi (Loc:S2 > S2 B2C > S2 B2C 84, Ext: +65 67904284) |
| Co-Supervisor | - |
| RI Co-Supervisor | - |
| Lab | Internet of Things Laboratory (Loc: S1-B4c-14, ext: 5470/5475) |
| Single/Group: | Single |
| Area: | Digital Media Processing and Computer Engineering |
| ISP/RI/SMP/SCP?: |