In the realm of data science, anomaly detection stands as a critical task, identifying unusual patterns that do not conform to expected behavior. Deep learning, a subset of machine learning ...

The anomaly detection script is designed to work with the MVTec dataset for identifying anomalies in manufacturing products. It supports several command line arguments to customize its execution, ...

You can create a release to package software, along with release notes and links to binary files, for other people to use. Learn more about releases in our docs ...

The Impact of Deep Learning on Anomaly Detection 6 minute read August 10, 2020. By. Xuning (Mike) Tang. ... Machine learning-based anomaly detection algorithms are a leap forward from the rule ...

Abstract: Anomaly detection in financial transactions is paramount for safeguarding against fraudulent activities that pose significant risks to financial institutions and customers alike. Traditional ...

Leveraging deep learning techniques, researchers have developed methods that are capable of automatically differentiating normal from abnormal patterns in image data.

Deep learning has transformed anomaly detection in precision agriculture by introducing architectures that can automatically learn hierarchical representations of crop health data Han et al. (2022).

Video anomaly detection is a crucial topic in the field of deep learning. Typically, manually monitoring abnormal behavior in surveillance videos is a labor-intensive task. As society advances, the ...

Using time-series data. Anomaly Detector works like most Azure platform services, offering a REST API that accepts JSON-formatted data.A C# SDK makes it easier to build code to work with the ...