Unsupervised Classification of Hydrophone Signals With an Improved Mel-Frequency Cepstral Coefficient Based on Measured Data Analysis.
Kunde YangXingyue ZhouPublished in: IEEE Access (2019)
Keyphrases
- unsupervised classification
- data analysis
- cepstral features
- supervised classification
- unsupervised learning
- data clustering
- clustering ensemble
- remote sensing data
- data mining
- machine learning
- remote sensing images
- k means
- hyperspectral images
- clustering analysis
- high dimensional data
- prediction accuracy
- image processing