Anomaly detection is the process of finding items in a dataset that are different in some way from the majority of the items. For example, you could examine a dataset of credit card transactions to ...
SHENZHEN, China - MicroCloud Hologram Inc. (NASDAQ: HOLO), a global provider of holographic technology services with a market capitalization of $28.76 million, has announced the optimization of its ...
Machines fail. By creating a time-series prediction model from historical sensor data, you can know when that failure is coming Anomaly detection covers a large number of data analytics use cases.
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Image-based model enhances the detection of surface defects in low-light industrial settings
In industry, the detection of anomalies such as scratches, dents, and discolorations is crucial to ensure product quality and safety. However, conventional methods rely on heavy computational ...
Dr. James McCaffrey of Microsoft Research provides full code and step-by-step examples of anomaly detection, used to find items in a dataset that are different from the majority for tasks like ...
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