… contexts, such as denoising AE [21], sparse … information with AE-based networks. Zabalza
et al. [38] proposed a novel segmented stacked AE (S-SAE) for hyperspectral feature extraction…

… feature extraction. The classifier uses controlled sampling and unbiased performance to
classify spatial-spectral features… to classify the HSI image using the principle of denoising by …

… of image, This article proposes a noise estimation method based on a stacked autoencoder.
… Furthermore, generalizing the proposed method to specific applications of noise removal …

… and spatial information contained in hyperspectral images (… for HSI classification based on
stacked autoencoder (SAE) and … for feature extraction, the dimensionality-reduced image was …

… The basic denoising autoencoder (DAE-1) and the stacked DAE (DAE-2) were studied
for … of denoising pixel-wise spectra of hyperspectral images using denoising autoencoder. …

… is put on the conventional image classification methods for hyper-spectral images. To fill this
… -based feature extraction method for hyper-spectral data classification. Firstly, we used a …

… information through appropriate feature extraction and feature selection methods thus reducing
data dimension to an appropriate scale. A deep learning-based … which can denoise as …

… Therefore, denoising is considered as an important preprocessing step for HSI analysis
and information retrieval [41]. Image denoising is the action of discarding noise from a noisy …

… -LR and the adaptive spatial information extraction method, we compare the performance
of the proposed method against that of the Stacked denoising autoencoder (SDAE), Linear …

… Accurate LULC information extracted from remotely sensed images have great contribution
in … express distinct characteristics that could be learned by a stacked denoising autoencoder (…