feature extraction; hyperspectral imaging; image classification; support vector machines; unsupervised learning; BCFE method; K-means clustering algorithm; LDA; PCA; SVM training; boundary clustering based feature extraction; high dimensional data classification; hyperspectral image classification; land cover class classification; linear discriminant analysis; principal component analysis; spectral information; support vector machines; unsupervised feature extraction method; Accuracy; Educational institutions; Feature extraction; Hyperspectral imaging; Principal component analysis; Support vector machines; Training; extraction-clustering-boundary; feature; sample-classification-hyperspectral image;
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