FAAD: an unsupervised fast and accurate anomaly detection method for a multi-dimensional sequence over data stream.
Bin LiYijie WangDongsheng YangYongmou LiXingkong MaPublished in: Frontiers Inf. Technol. Electron. Eng. (2019)
Keyphrases
- detection method
- multi dimensional
- data streams
- multi dimensional data
- detection algorithm
- face detection
- feature detection
- sliding window
- sequential data
- change detection
- outlier detection
- anomaly detection
- sequential pattern mining
- unsupervised learning
- data sets
- image processing
- saliency detection
- range queries
- concept drift
- streaming data
- transactional data
- data stream management systems
- continuous queries
- data cube
- data distribution
- query processing
- face recognition
- image segmentation