309
edits
(→Topics) |
(→Topics) |
||
Line 63: | Line 63: | ||
| [https://ieeexplore.ieee.org/abstract/document/8638062] | | [https://ieeexplore.ieee.org/abstract/document/8638062] | ||
|- | |- | ||
| | | Anomaly Detection for Road Traffic(assigned) | ||
| | | Anomaly detection on road traffic has vast application prospects in urban traffic management and road safety. Due to the impact of many factors such as weather, viewpoints and road conditions in the real-world traffic scene, anomaly detection still faces many challenges. There are many causes for vehicle anomalies, such as crashes, vehicle on fires and vehicle faults, which exhibits different unknown behaviors. In this course, we need to learn efficient anomaly detection systems of the state-of-the-art and understand their design and implementation. | ||
| Programming skills. Interested in this topic, willing to follow the advisor's guidance, patience and time for reading multiple papers | | Programming skills. Interested in this topic, willing to follow the advisor's guidance, patience and time for reading multiple papers | ||
| [Yali Yuan, yali.yuan@cs.informatik.uni-goettingen.de] | | [Yali Yuan, yali.yuan@cs.informatik.uni-goettingen.de] | ||
| [https:// | | [https://github.com/ShuaiBai623/AI-City-Anomaly-Detection] | ||
|- | |- | ||
| Failure recovery from the breakpoint in service function chain | | Failure recovery from the breakpoint in service function chain |