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

Various machine learning and deep learning techniques have been proposed for
classification purposes in the case of hyperspectral imaging. Among all the machine …

Hyperspectral image (HSI) classification is one of the most important tasks in hyperspectral
data analysis. Convolutional neural networks (CNN) have been introduced to HSI …

Hyperspectral image classification (HSIC) methods based on convolutional neural network
(CNN) continue to progress in recent years. However, high complexity, information …

高分辨率遥感影像解译是遥感信息处理领域的研究热点之一, 在遥感大数据知识挖掘与智能化
分析中起着至关重要的作用, 具有重要的民用和军事应用价值. 传统的高分辨率遥感影像解译 …

Convolutional neural networks (CNN) have led to a successful breakthrough for
hyperspectral image classification (HSIC). Due to the intrinsic spatial-spectral specificities of …

Despite various approaches proposed to smooth the hyperspectral images (HSIs) before
feature extraction, the efficacy is still affected by the noise, even using the corrected dataset …

Convolutional neural networks (CNNs) have recently been demonstrated to be a powerful
tool for hyperspectral image (HSI) classification, since they adopt deep convolutional layers …

Despite success in the same-scene hyperspectral image classification (HSIC), for the cross-
scene classification, samples between source and target scenes are not drawn from the …

Hyperspectral dimensionality reduction (HDR), an important preprocessing step prior to high-
level data analysis, has been garnering growing attention in the remote sensing community …