From tensors to novelties: Low-dimensional representations for anomaly detection in multispectral imagery

Key Points

• Anomaly detection improved with low-dimensional representations, enhancing detection accuracy.
• Key evidence shows a significant reduction in false positive rates, compared to traditional methods.
• The approach incorporates tensor decomposition techniques for effective feature extraction.
• Findings suggest that these methods may lead to better real-time applications in various fields.