ESTIMATING OPTIMAL NUMBER OF COMPRESSIVELY SENSED BANDS FOR HYPERSPECTRAL CLASSIFICATION VIA FEATURE SELECTION

Estimating Optimal Number of Compressively Sensed Bands for Hyperspectral Classification via Feature Selection

Compressive sensing (CS) has received considerable interest in hyperspectral sensing.Recent articles have also exploited the benefits of CS in hyperspectral image classification (HSIC) in the compressively sensed band domain (CSBD).However, on Compact Refrigerator many occasions, the requirement of full bands is not necessary for HSIC to perform we

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