Hyperspectral change detection (CD) can be effectively performed using deep-learning
networks. Although these approaches require qualified training samples, it is difficult to …

Amyloidopathic disorders such as Alzheimer's disease present symptomology years after
the entrenchment of amyloidogenic imbalance. The pathologic α-helix→ β-strand …

This study aims to evaluate three classes of methods to discriminate between 13 peatland
vegetation types using reflectance data. These vegetation types were empirically defined …

Spectral Information Divergence (SID) was identified as the most efficient spectral similarity
measure. However, we show that divergence are not adapted to direct use on spectra …

Determining foliar mineral status of tissue cultured shoots can be costly and time consuming,
yet hyperspectral signatures might be useful for determining mineral contents of these …

The spectral reflectance of any pixel in a remote sensing image depends on the
characteristics of the particular land cover (LC) present in the Instantaneous Field of View …

Due to the lack of training samples, hyperspectral classification often adopts the minimum
distance classification method based on spectral metrics. This paper proposes a novel …

In the recent years, electrical, electronics, and telecommunications have far-famed a rare
improvement, the quantity of nonlinear loads has inflated. Many electric power consumption …

Native plants are very important in urban landscape systems, as they have been adopted to
the environment and are resistant to different biotic or abiotic stresses in the area. Little-leaf …

The increasing use of products based on airborne hyperspectral data for decision-making
calls for a thorough quality assessment. Due to the complexity of the corresponding …