Anomaly detection of hyperspectral images based on improved isolation forest algorithm
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Research on anomaly detection in hyperspectral images has been conducted, with a focus on improving the isolation forest algorithm. Other related studies have explored various image processing techniques, including real-time medical image enhancement and adaptive multi-feature fusion for image registration. The scope of these studies appears to be broad, encompassing applications in fields such as medicine, agriculture, and remote sensing, with multiple research papers published in scientific journals.
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