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Multiscale Superpixel-Based Hyperspectral Image Classification Using Recurrent Neural Networks With Stacked Autoencoders

https://doi.org/10.1109/tmm.2019.2928491

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Linear Discriminant Analysis

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Single image super resolution using local smoothness and nonlocal self-similarity priors

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Learning multiscale and deep representations for classifying remotely sensed imagery

inferredcites →https://doi.org/10.1016/j.isprsjprs.2017.08.011openalex-snapshot

Contextually guided very-high-resolution imagery classification with semantic segments

inferredcites →https://doi.org/10.1016/j.neucom.2018.03.012openalex-snapshot

Multi-scale hierarchical recurrent neural networks for hyperspectral image classification

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Segmentation and classification of hyperspectral images using watershed transformation

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Towards better exploiting convolutional neural networks for remote sensing scene classification

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Hyperspectral image reconstruction by deep convolutional neural network for classification

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Guided filter based Deep Recurrent Neural Networks for Hyperspectral Image Classification

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Learning selfhood scales for urban land cover mapping with very-high-resolution satellite images

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Multi-scale superpixel spectral–spatial classification of hyperspectral images

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Classification of hyperspectral data using extended attribute profiles based on supervised and unsupervised feature extraction techniques

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Spectral–spatial classification of hyperspectral images using deep convolutional neural networks

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On combining multiscale deep learning features for the classification of hyperspectral remote sensing imagery

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Gradient-based learning applied to document recognition

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Local Discriminant Embedding and Its Variants

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Inside-Outside Net: Detecting Objects in Context with Skip Pooling and Recurrent Neural Networks

inferredcites →https://doi.org/10.1109/igarss.2010.5649222openalex-snapshot

A multiple classifier approach for spectral-spatial classification of hyperspectral data

inferredcites →https://doi.org/10.1109/igarss.2015.7326945openalex-snapshot

Deep supervised learning for hyperspectral data classification through convolutional neural networks

inferredcites →https://doi.org/10.1109/igarss.2015.7326948openalex-snapshot

Spectral-spatial hyperspectral image classification via superpixel merging and sparse representation

inferredcites →https://doi.org/10.1109/jstars.2013.2252150openalex-snapshot

Spatial-Spectral Kernel Sparse Representation for Hyperspectral Image Classification

inferredcites →https://doi.org/10.1109/jstars.2014.2329330openalex-snapshot

Deep Learning-Based Classification of Hyperspectral Data

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Spectral–Spatial Classification of Hyperspectral Data Based on Deep Belief Network

inferredcites →https://doi.org/10.1109/jstars.2016.2517204openalex-snapshot

Spectral–Spatial Classification of Hyperspectral Image Based on Deep Auto-Encoder

inferredcites →https://doi.org/10.1109/jstars.2017.2680324openalex-snapshot

Object-Based Convolutional Neural Network for High-Resolution Imagery Classification

inferredcites →https://doi.org/10.1109/lgrs.2005.857031openalex-snapshot

Composite Kernels for Hyperspectral Image Classification

inferredcites →https://doi.org/10.1109/lgrs.2008.2001282openalex-snapshot

Limitations of Principal Components Analysis for Hyperspectral Target Recognition

inferredcites →https://doi.org/10.1109/lgrs.2010.2047711openalex-snapshot

SVM- and MRF-Based Method for Accurate Classification of Hyperspectral Images

inferredcites →https://doi.org/10.1109/lgrs.2017.2737823openalex-snapshot

Recursive Autoencoders-Based Unsupervised Feature Learning for Hyperspectral Image Classification

inferredcites →https://doi.org/10.1109/tcyb.2015.2453359openalex-snapshot

Learning Hierarchical Spectral–Spatial Features for Hyperspectral Image Classification

inferredcites →https://doi.org/10.1109/tgrs.2004.842478openalex-snapshot

Classification of hyperspectral data from urban areas based on extended morphological profiles

inferredcites →https://doi.org/10.1109/tgrs.2011.2153861openalex-snapshot

Hyperspectral Image Classification With Independent Component Discriminant Analysis

inferredcites →https://doi.org/10.1109/tgrs.2011.2165957openalex-snapshot

Locality-Preserving Dimensionality Reduction and Classification for Hyperspectral Image Analysis

inferredcites →https://doi.org/10.1109/tgrs.2012.2230268openalex-snapshot

Generalized Composite Kernel Framework for Hyperspectral Image Classification

inferredcites →https://doi.org/10.1109/tgrs.2015.2392755openalex-snapshot

Spectral–Spatial Classification of Hyperspectral Images With a Superpixel-Based Discriminative Sparse Model

inferredcites →https://doi.org/10.1109/tgrs.2015.2421638openalex-snapshot

Efficient Superpixel-Level Multitask Joint Sparse Representation for Hyperspectral Image Classification

inferredcites →https://doi.org/10.1109/tgrs.2015.2445767openalex-snapshot

Classification of Hyperspectral Images by Exploiting Spectral–Spatial Information of Superpixel via Multiple Kernels

inferredcites →https://doi.org/10.1109/tgrs.2016.2530807openalex-snapshot

Discriminative Multiple Kernel Learning for Hyperspectral Image Classification

inferredcites →https://doi.org/10.1109/tgrs.2016.2543748openalex-snapshot

Spectral–Spatial Feature Extraction for Hyperspectral Image Classification: A Dimension Reduction and Deep Learning Approach

inferredcites →https://doi.org/10.1109/tgrs.2016.2584107openalex-snapshot

Deep Feature Extraction and Classification of Hyperspectral Images Based on Convolutional Neural Networks

inferredcites →https://doi.org/10.1109/tgrs.2016.2603190openalex-snapshot

Probabilistic Fusion of Pixel-Level and Superpixel-Level Hyperspectral Image Classification

inferredcites →https://doi.org/10.1109/tgrs.2016.2616355openalex-snapshot

Hyperspectral Image Classification Using Deep Pixel-Pair Features

inferredcites →https://doi.org/10.1109/tgrs.2016.2636241openalex-snapshot

Deep Recurrent Neural Networks for Hyperspectral Image Classification

inferredcites →https://doi.org/10.1109/tip.2011.2175741openalex-snapshot

Spectral–Spatial Classification of Hyperspectral Data Based on a Stochastic Minimum Spanning Forest Approach

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Large-Margin Multi-Modal Deep Learning for RGB-D Object Recognition

inferredcites →https://doi.org/10.1109/tmm.2016.2599145openalex-snapshot

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inferredcites →https://doi.org/10.1162/neco.2006.18.7.1527openalex-snapshot

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Dimensionality Reduction of Multimodal Labeled Data by Local Fisher Discriminant Analysis

inferredcites →https://doi.org/10.7551/mitpress/7503.003.0024openalex-snapshot

Greedy Layer-Wise Training of Deep Networks

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Flow-Based Density Estimation for Hyperspectral Anomaly Detection

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Hyperspectral Image Classification Method Based on 2D–3D CNN and Multibranch Feature Fusion

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Hyperspectral Image Classification Via Spectral-Spatial Random Patches Network

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A Survey on Superpixel Segmentation as a Preprocessing Step in Hyperspectral Image Analysis

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Locally Homogeneous Covariance Matrix Representation for Hyperspectral Image Classification

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inferred← citeshttps://doi.org/10.3934/mbe.2023510openalex-snapshot

Image classification of hyperspectral remote sensing using semi-supervised learning algorithm

inferred← citeshttps://doi.org/10.48550/arxiv.2108.08607openalex-snapshot

Generating Superpixels for High-resolution Images with Decoupled Patch Calibration

inferred← citeshttps://doi.org/10.5194/gi-2022-24openalex-snapshot

Sample labeling and classification method of hyperspectral remote sensing images based on texture features and semi-supervised learning

inferred← citeshttps://doi.org/10.5194/gi-2022-24-ac1openalex-snapshot

Reply on RC1

inferred← citeshttps://doi.org/10.5194/gi-2022-24-ac2openalex-snapshot

Reply on RC2

inferred← citeshttps://doi.org/10.5194/gi-2022-24-ac3openalex-snapshot

Reply on CC1

inferred← citeshttps://doi.org/10.5194/gi-2022-24-ac4openalex-snapshot

Reply on CC2

inferred← citeshttps://doi.org/10.5194/gi-2022-24-cc1openalex-snapshot

Comment on gi-2022-24

inferred← citeshttps://doi.org/10.5194/gi-2022-24-cc2openalex-snapshot

Comment on gi-2022-24

inferred← citeshttps://doi.org/10.5194/gi-2022-24-rc1openalex-snapshot

Comment on gi-2022-24

inferred← citeshttps://doi.org/10.5194/gi-2022-24-rc2openalex-snapshot

Comment on gi-2022-24

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