The electrocardiogram (ECG) is a widely used, noninvasive test for analyzing arrhythmia.
However, the ECG signal is prone to contamination by different kinds of noise. Such noise …

This paper proposes a data-driven approach for optimal power flow (OPF) based on the
stacked extreme learning machine (SELM) framework. SELM has a fast training speed and …

Direct prediction of material properties from microstructures through statistical models has
shown to be a potential approach to accelerating computational material design with large …

Hyperspectral image sensors capture surface reflectance over a range of wavelengths. The
fine spectral information is recorded in terms of hundreds of bands. Hyperspectral image …

The objective of this research was to develop a deep learning method which consisted of
stacked auto-encoders (SAE) and fully-connected neural network (FNN) for predicting …

Limited by the shape-fixed kernels, convolutional neural networks (CNNs) are usually
difficult to model difform land covers in hyperspectral images (HSIs), leading to inadequate …

摘要高光谱图像(Hyperspectral imagery, HSI) 分类是高光谱遥感对地观测技术的一项重要内容,
在军事及民用领域都有着重要的应用. 然而, 高光谱图像的高维特性, 波段间高度相关性 …

This paper presents a dual autoencoder network model based on the retinex theory to
perform the low-light enhancement and noise reduction by combining the stacked and …

Rice diseases are major threats to rice yield and quality. Rapid and accurate detection of
rice diseases is of great importance for precise disease prevention and treatment. Various …

Most traditional approaches classify hyperspectral image (HSI) pixels relying only on the
spectral values of the input channels. However, the spatial context around a pixel is also …