… Stacked denoising autoencoders:learning useful representations in a deep network with
a local denoising criterion[J]. Journal of machine learning research, 2010, 11(12):3371-408. …

… Stacked denoise autoencoder based feature extraction and classification for hyperspectral
images. Journal of Sensors, 2016, 2016: Article No. 3632943 82 Liu YZ, Cao G, Sun QS, …

… 堆栈式自编码器(stacked auto-encoder, SAE) [17] ,堆栈降噪自编码机(stacked denoise auto-encoder,
SDAE) [18] 和无监督稀疏自编码机(unsupervised convolutional sparse auto-encoder, …

… Unsupervised image segmentation via Stacked Denoising Auto-encoder and hierarchical …
data and image information of hyperspectral image, and then deep feature extracted by SAE …

… hyperspectral images and inaccurate target feature extraction, a variable-Wise Weighted
Stacked Autoencoder (VW-SAE) spectral data feature … Based on the stacked autoencoder (SAE)…

… Abstract: Feature extraction is a key step in radar target recognition. The … based on stacked
denoising sparse autoencoder is proposed in this paper. This method can extract features …

… Abstract To extract rich features of hyperspectral image, this study explores the deep features
of the raw data by using a stacked sparse autoencoder in the deep learning theory. First …

… Deep feature extraction and classification of hyperspectral images based on convolutional
… Stacked denoising autoencoders: learning useful representations in a deep network with a …

… spectral and spatial features of hyperspectral images. This model also achieves unsupervised
feature extraction without … Stacked autoencoder-based deep learning for remote-sensing …

… A combined model based on stacked autoencoders and fractional Fourier entropy for … Fault
feature extraction and diagnosis of rolling bearings based on wavelet thresholding denoising …