首页>
外国专利>
IMAGE-BASED ANOMALY DETECTION FOR AERIAL INSPECTION USING SELF-SUPERVISED LEARNING
IMAGE-BASED ANOMALY DETECTION FOR AERIAL INSPECTION USING SELF-SUPERVISED LEARNING
展开▼
机译:使用自学习的基于图像的航空检测异常检测
展开▼
页面导航
摘要
著录项
相似文献
摘要
A method of automatically detecting anomaly from aerial images of an object of interest is provided. The method may include generating a data coding model corresponding to a category of assets by training a neural network with a training set of digital images depicting an asset in a state that is free from anomalies. The method may further include receiving a target digital image depicting a target asset, and reconstructing the target digital image using the data coding model to generate a decoded target digital image associated with the state that is free from anomalies. The data coding model may be self-supervised to learn to reconstruct itself to an anomaly-free state. The method may also include comparing the target digital image to the decoded target digital image to generate a difference map and, in response to a determination that the difference map depicts any anomaly, generating anomaly alert data.
展开▼