Proposed unsupervised framework for industrial anomaly detection (IMAGE)

Shibaura Institute of Technology

Proposed unsupervised framework for industrial anomaly detection

Caption

The proposed industrial anomaly detection model is computationally efficient, memory-friendly, and also suitable for low-light conditions, common in manufacturing environments, making it well-suited for real-time industrial applications.

Credit

Dr. Phan Xuan Tan from SIT, Japan Source Link: https://doi.org/10.1093/jcde/qwaf043

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License

CC BY-NC

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