[PDF] Top 20 Multiscale spatial-spectral convolutional network with image-based framework for hyperspectral imagery classification
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Multiscale spatial-spectral convolutional network with image-based framework for hyperspectral imagery classification
... extract multiscale spatial structures and proposed an unsupervised cooperative sparse autoencoder method to fuse deep spatial features and spectral ...information. Multiscale feature ... See full document
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Spatial-spectral classification of hyperspectral images : a deep learning framework with Markov random fields based modeling
... as image processing, natural language understanding, speech recognition and artificial intelligence ...sensing image analysis, classification and target detection, deep learning has also been ... See full document
12
Classification of Hyperspectral Image Based on Double-Branch Dual-Attention Mechanism Network
... mechanism network was proposed for HSI classification, which is equipped with two branches to capture spectral feature and spatial feature severally and densely connected 3D convolution layer to ... See full document
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Deep Pyramidal Residual Networks for Spectral-Spatial Hyperspectral Image Classification
... residual network model based on pyramidal bottleneck residual units to achieve fast and accurate HSI analysis and classification, using both spectral and spatial ...stacked ... See full document
22
Unsupervised Spectral-Spatial Feature Learning via Deep Residual Conv-Deconv Network for Hyperspectral Image Classification
... unsupervised spectral–spatial feature learning, which has a quick access to arbitrary amounts of unlabeled data, is conceptually of high ...unsupervised convolutional network for learning ... See full document
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Spectral-spatial feature learning for hyperspectral imagery classification using deep stacked sparse autoencoder
... hybrid framework of PCA, guided filtering, and stacked autoencoder as an efficient deep learning architecture for hyperspectral data ...– spatial hyperspectral image ... See full document
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A Novel Method for Remotely Sensed Hyperspectral Image Classification Based on Convolutional Neural Network
... HSI classification a challenging problem. The major steps of image classification may include determination of a suitable classification system, selection of training samples, image ... See full document
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Spatial-spectral classification of hyperspectral images : a deep learning framework with Markov random fields based modeling
... as image processing, natural language understanding, speech recognition and artificial intelligence ...sensing image analysis, classification and target detection, deep learning has also been ... See full document
13
Learning to Pay Attention on Spectral Domain: A Spectral Attention Module-Based Convolutional Network for Hyperspectral Image Classification
... years, hyperspectral image classification using convolutional neural networks (CNNs) has progressed ...that hyperspectral images are of high dimensionality, CNNs can be hindered by ... See full document
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Spectral Classification of a Set of Hyperspectral Images using the Convolutional Neural Network, in a Single Training
... Abstract—Hyperspectral imagery has seen a great evolution in recent ...automatic classification of these hyperspectral images with a high rate and in an acceptable ...several ... See full document
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Spectral-Spatial Classification Integrating Band Selection for Hyperspectral Imagery With Severe Noise Bands
... improve classification performance, spatial information of hyperspectral imagery can be additionally ...The spectral-spatial classification approaches comprehensively uti- ... See full document
13
Spectral Angle Based Unary Energy Functions for Spatial-Spectral Hyperspectral Classification Using Markov Random Fields
... Hyperspectral classification is the process of identifying the material present under each pixel in a hyperspectral ...a hyperspectral image, is dependent on the chemical structure of ... See full document
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Spectral-spatial classification of hyperspectral data using spectral-domain local binary patterns
... 10 Li, Jun, et al. "Generalized Composite Kernel Framework for Hyperspectral Image Classification." IEEE Transactions on Geoscience & Remote Sensing 51.9(2013):4816-4829. 11 ... See full document
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Unsupervised spectral sub-feature learning for hyperspectral image classification
... In recent years, unsupervised learning methods for dimensionality reduction, such as isomap (Tenenbaum, De Silva, and Langford 2000), locally linear embedding (LLE) (Roweis and Saul 2000), Laplacian eigenmaps (LE) ... See full document
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Combined Features based Spatial Composite Kernel Formation for Hyperspectral Image Classification
... But Run Length features fail to distinguish the classes which contain more or less same textural properties. For identifying those classes, which are outliers while using the traditional Run Length features, Principal ... See full document
9
Superpixel based feature specific sparse representation for spectral-spatial classification of hyperspectral images
... SRC-based framework, the computational complexity can be even higher due to the large size of the dictionary to be constructed from the training samples in most ...the classification accuracy. Within ... See full document
17
Histopathological Biopsy Image Classification Based On Convolutional Neural Network
... cells. Framework is divided into two segments: Training phase and testing ...in classification of histopathological image are as follow: pre-processing, conversions of images into Gray and HSV form, ... See full document
6
Spectral–Spatial Classification of Hyperspectral Images Based on Hidden Markov Random Fields
... Conventional spectral classifiers treat hyperspectal images as a list of spectral measurements ...the classification of high dimensional data sets [4] and their considerable capability for handling ... See full document
11
Spectral Spatial Hyperspectral Image Classification based on Randomized Singular Value Decomposition and 3 Dimensional Discrete Wavelet Transform
... utilize spatial-filtering method and spatial smoothness prior of ...the spatial correlation under HSIs can be fully ...the spectral-spatial features and the probabilistic SVM is used to ... See full document
10
Spectral-spatial classification of hyperspectral data using spectral-domain local binary patterns
... in spectral-spatial features classification for hyperspectral images (HSI) with high spatial ...novel Spectral-spatial classification method for improving ... See full document
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