Name
Abstract | ||
|---|---|---|
Detection of outliers and anomalous behavior is a well-known problem in the data mining and statistics fields. Although the problem of identifying single outliers has been extensively studied in the literature, little effort has been devoted to detecting small groups of outliers that are similar to each other but markedly different from the entire population. Many real-world scenarios have small g... |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/MCG.2014.78 | IEEE Computer Graphics and Applications |
Keywords | Field | DocType |
Nuclear magnetic resonance,Data mining,Biomedical image processing,Computer graphics,Data visulaization,Cells (biology),Biological cells,Pathological processes | Population,Data mining,Anomaly detection,Visualization,Computer science,Outlier,Visual analytics,Ground truth,Cluster analysis,Rare events | Journal |
Volume | Issue | ISSN |
35 | 3 | 0272-1716 |
Citations | PageRank | References |
2 | 0.39 | 4 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Enikö Székely | 1 | 2 | 0.73 |
| Arnaud Sallaberry | 2 | 147 | 14.86 |
| Faraz Zaidi | 3 | 2 | 0.39 |
| Pascal Poncelet | 4 | 768 | 126.47 |