Annotation-efficient image anomaly detection
The present invention proposes a method for detecting anomalous or out-of-distribution images in a machine learning system (1) comprising a pre-training network with a first encoder, and an anomaly detection network with a second encoder. The system is first pre-trained by training the pre-training network, and then subsequently fine-tuned by training the anomaly detection network. According to one example, during pre-training, only unlabelled training images are used, while during fine-tuning, a small fraction of labelled training images is used in addition to unlabelled training images. The method can be applied to both single and multi-domain image data.
74561938
Alternative title(s) : (fr) Détection d'anomalies d'images efficiente du point de vue des annotations
TTO:6.2103
Patent number | Country code | Kind code | Date issued |
US2024185582 | US | A1 | 2024-06-06 |
EP4285281 | EP | A1 | 2023-12-06 |
WO2022162427 | WO | A1 | 2022-08-04 |