Anomaly detection
Approach in data analysis
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MAU-GPT (1) · Anomaly detection (1) · Industrial automation (1) · Machine learning (1) · Product inspection (1) · arXiv (1) · Computer vision (1)
📖 Key Information
In data analysis, anomaly detection (also referred to as outlier detection and sometimes as novelty detection) is generally understood to be the identification of rare items, events or observations which deviate significantly from the majority of the data and do not conform to a well defined notion of normal behavior. Such examples may arouse suspicions of being generated by a different mechanism, or appear inconsistent with the remainder of that set of data.
Anomaly detection finds application in many domains including cybersecurity, medicine, machine vision, statistics, neuroscience, law enforcement and financial fraud to name only a few.
📰 Related News (1)
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🇺🇸 MAU-GPT: Enhancing Multi-type Industrial Anomaly Understanding via Anomaly-aware and Generalist Experts Adaptation
arXiv:2602.07011v1 Announce Type: cross Abstract: As industrial manufacturing scales, automating fine-grained product image analysis has become criti...
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People and organizations frequently mentioned alongside Anomaly detection:
- 🌐 Machine learning (1 shared articles)
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- 🌐 Computer vision (1 shared articles)