… Stackeddenoiseautoencoderbasedfeatureextraction and classification for hyperspectral images. Journal of Sensors, 2016, 2016: Article No. 3632943 82 Liu YZ, Cao G, Sun QS, …
孙俊, 靳海涛, 芦兵, 武小红… - Transactions of the …, 2019 - search.ebscohost.com
… Unsupervised image segmentation via StackedDenoisingAuto-encoder and hierarchical … data and imageinformation of hyperspectralimage, and then deep featureextracted by SAE …
… hyperspectralimages and inaccurate target featureextraction, a variable-Wise Weighted StackedAutoencoder (VW-SAE) spectral data feature … Based on the stackedautoencoder (SAE)…
… Abstract: Featureextraction 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 hyperspectralimage, this study explores the deep features of the raw data by using a stacked sparse autoencoder in the deep learning theory. First …
… Deep featureextraction and classification of hyperspectralimagesbased on convolutional … Stackeddenoisingautoencoders: learning useful representations in a deep network with a …
… spectral and spatial features of hyperspectralimages. This model also achieves unsupervised featureextraction without … Stackedautoencoder-based deep learning for remote-sensing …
孙俊, 张林, 周鑫, 武小红, 沈继锋… - Transactions of the …, 2021 - search.ebscohost.com
… A combined model based on stackedautoencoders and fractional Fourier entropy for … Fault featureextraction and diagnosis of rolling bearings based on wavelet thresholding denoising …