All Outputs (2)

PCA-domain fused singular spectral analysis for fast and noise-robust spectral-spatial feature mining in hyperspectral classification. (2021)
Journal Article
YAN, Y., REN, J., LIU, Q., ZHAO, H., SUN, H. and ZABALZA, J. 2023. PCA-domain fused singular spectral analysis for fast and noise-robust spectral-spatial feature mining in hyperspectral classification. IEEE geoscience and remote sensing letters [online], 20, article 5505405. Available from: https://doi.org/10.1109/LGRS.2021.3121565

The principal component analysis (PCA) and 2-D singular spectral analysis (2DSSA) are widely used for spectral domain and spatial domain feature extraction in hyperspectral images (HSI). However, PCA itself suffers from low efficacy if no spatial inf... Read More about PCA-domain fused singular spectral analysis for fast and noise-robust spectral-spatial feature mining in hyperspectral classification..

Nondestructive phenolic compounds measurement and origin discrimination of peated barley malt using near-infrared hyperspectral imagery and machine learning. (2021)
Journal Article
YAN, Y., REN, J., TSCHANNERL, J., ZHAO, H., HARRISON, B. and JACK, F. 2021. Nondestructive phenolic compounds measurement and origin discrimination of peated barley malt using near-infrared hyperspectral imagery and machine learning. IEEE transactions on instrumentation and measurement [online], 70, article 5010715. Available from: https://doi.org/10.1109/TIM.2021.3082274

Quantifying phenolic compound in peated barley malt and discriminating its origin are essential to maintain the aroma of high-quality Scottish whisky during the manufacturing process. The content of the total phenol varies in peated barley malts, whi... Read More about Nondestructive phenolic compounds measurement and origin discrimination of peated barley malt using near-infrared hyperspectral imagery and machine learning..