Scan Statistics for the Detection of Anomalies in M -Dependent Random Fields with Applications to Image Data
M 依赖随机场异常检测的扫描统计量及图像应用
Anomaly detection in random fields is an important problem in many applications including the detection of cancerous cells in medicine, obstacles in autonomous driving and cracks in the construction material of buildings. Such anomalies are often visible as areas with different expected values compared to the background noise. Scan statistics based on local means have the potential to detect such local anomalies by enhancing relevant features. We derive limit theorems for a…