Recent imaging science and technology discoveries have considered hyperspectral
imagery and remote sensing. The current intelligent technologies, such as support vector …

The track of medical imaging has witnessed several advancements in the last years. Several
medical imaging modalities have appeared in the last decades including X-ray, Computed …

Convolutional neural networks are widely used in the field of hyperspectral image
classification because of their excellent nonlinear feature extraction ability. However, as the …

The precise classification of land covers with hyperspectral imagery (HSI) is a major
research-focused topic in remote sensing, especially using unmanned aerial vehicle (UAV) …

As an essential reprocessing method, dimensionality reduction (DR) can reduce the data
redundancy and improve the performance of hyperspectral image (HSI) classification. A …

Due to the cubic structure of a hyperspectral image (HSI), how to characterize its spectral
and spatial properties in 3-D is challenging. Conventional spectral–spatial methods usually …

Drought can significantly affect the carbon cycle of ecosystems. The Qinba Mountains region
has a high potential for developing carbon sink forestry due to its strong carbon fixation …

Abstract Background and Objective Medical hyperspectral images (MHSIs) are used for a
contact-free examination of patients without harmful radiation. However, high-dimensionality …

Hyperspectral imaging is highly important with respect to the detection, identification and
classification of various natural resources—minerals, earth's natural eruptions, vegetation …

For multimodal medical image fusion problems, most of the existing fusion approaches are
based on pixel-level. However, the pixel-based fusion method tends to lose local and spatial …