Land-use and land-cover change (LULCC) are of importance in natural resource
management, environmental modelling and assessment, and agricultural production …

Recent advances in airborne and spaceborne hyperspectral imaging technology have
provided end users with rich spectral, spatial, and temporal information. They have made a …

Alfalfa is a valuable and intensively produced forage crop in the United States, and the
timely estimation of its yield can inform precision management decisions. However …

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

Owing to the powerful data representation ability of deep learning (DL) techniques,
tremendous progress has been recently made in hyperspectral image (HSI) classification …

Several bandwise total variation (TV) regularized low-rank (LR)-based models have been
proposed to remove mixed noise in hyperspectral images (HSIs). These methods convert …

High-throughput estimation of phenotypic traits from UAV (unmanned aerial vehicle) images
is helpful to improve the screening efficiency of breeding maize. Accurately estimating …

This paper studies the hyperspectral image (HSI) denoising problem under the assumption
that the signal is low in rank. In this paper, a mixture of Gaussian noise and sparse noise is …

Artificial Intelligence is a technique of modeling a computer, a computer administered-robot,
in the indistinguishable manner the acute humans reflect. Machine Learning is a mechanism …

Learning from a limited number of labeled samples (pixels) remains a key challenge in the
hyperspectral image (HSI) classification. To address this issue, we propose a deep metric …