The key elements that underpin food security require the adaptation of agricultural systems
to support productivity increases while minimizing inputs and the adverse effects of climate …

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

Unsupervised feature selection attempts to select a small number of discriminative features
from original high-dimensional data and preserve the intrinsic data structure without using …

随着模式识别, 机器学习, 遥感技术等相关学科领域的发展, 高光谱遥感影像分类研究取得快速
进展. 本文系统总结和评述了当前高光谱遥感影像分类的相关研究进展, 在总结分类策略的基础 …

The recent developments in the modern data collection tools, techniques, and storage
capabilities are leading towards huge volume of data. The dimensions of data indicate the …

Hyperspectral (HS) imaging, also known as image spectrometry, is a landmark technique in
geoscience and remote sensing (RS). In the past decade, enormous efforts have been made …

By considering the spectral signature as a sequence, recurrent neural networks (RNNs)
have been successfully used to learn discriminative features from hyperspectral images …

Feature extraction is of significance for hyperspectral image (HSI) classification. Compared
with conventional hand-crafted feature extraction, deep learning can automatically learn …

The abundant spatial and contextual information provided by the advanced remote sensing
technology has facilitated subsequent automatic interpretation of the optical remote sensing …

Hyperspectral remote sensing technology has advanced significantly in the past two
decades. Current sensors onboard airborne and spaceborne platforms cover large areas of …