| Proj No. | A3202-251 |
| Title | Anomaly Detection: Comparing Different Machine Learning Approaches |
| Summary | Anomaly detection refers to identifying unusual patterns that do not conform to expected behavior. This is crucial in various fields such as fraud detection, network security, and quality control. The student should (1) carry out a literature survey on the topic, (2) either download an existing program or code a new program for an existing approach, and (3) summerize and compare the advantages and disadvantages of different machine learning approaches to anomaly detection. |
| Supervisor | A/P Wang Lipo (Loc:S1 > S1 B1C > S1 B1C 98, Ext: +65 67906372) |
| Co-Supervisor | - |
| RI Co-Supervisor | - |
| Lab | Computer Engineering I (Loc: S2-B4c-15) |
| Single/Group: | Single |
| Area: | Digital Media Processing and Computer Engineering |
| ISP/RI/SMP/SCP?: |