To address the issue that existing wireless sensor network (WSN)-based anomaly detection methods only consider and analyze temporal features, in this article, a self-supervised learning-based ...

Outlier detection is the task of classifying test data that differ in some respect from the data that are available during training. This may be seen as one-class classification, in which a model is ...

Developing a sensitive and efficient detection method for BACE1 activity is significant for AD progression evaluation. Due to the poor cleavage efficiency and acidic working conditions of BACE1, ...