Unsupervised detection of ash dieback disease (Hymenoscyphus fraxineus) using diffusion-based hyperspectral image clustering.
Sam L. PolkAland H. Y. ChanKangning CuiRobert J. PlemmonsDavid A. CoomesJames M. MurphyPublished in: CoRR (2022)
Keyphrases
- hyperspectral images
- target detection
- unsupervised learning
- clustering algorithm
- hyperspectral
- hyperspectral imaging
- k means
- remote sensing
- hyperspectral imagery
- detection method
- clustering method
- object detection
- computer vision
- false alarms
- detection algorithm
- data points
- high dimensional data
- dimensionality reduction
- multiscale
- high quality
- hyperspectral image classification
- document clustering
- detection rate
- co occurrence
- pattern recognition
- hyperspectral data
- machine learning