Toward generalist anomaly detection via in-context residual learning with few-shot sample prompts
This paper explores the problem of Generalist Anomaly Detection (GAD) aiming to train one
single detection model that can generalize to detect anomalies in diverse datasets from …
single detection model that can generalize to detect anomalies in diverse datasets from …
Deep one-class classification via interpolated gaussian descriptor
One-class classification (OCC) aims to learn an effective data description to enclose all
normal training samples and detect anomalies based on the deviation from the data …
normal training samples and detect anomalies based on the deviation from the data …