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Graph Convolutional Networks for Hyperspectral Image Classification
Convolutional neural networks (CNNs) have been attracting increasing att...
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Coupled Convolutional Neural Network with Adaptive Response Function Learning for Unsupervised Hyperspectral Super-Resolution
Due to the limitations of hyperspectral imaging systems, hyperspectral i...
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Spectral Superresolution of Multispectral Imagery with Joint Sparse and Low-Rank Learning
Extensive attention has been widely paid to enhance the spatial resoluti...
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Guided Deep Decoder: Unsupervised Image Pair Fusion
The fusion of input and guidance images that have a tradeoff in their in...
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Spatial-Spectral Manifold Embedding of Hyperspectral Data
In recent years, hyperspectral imaging, also known as imaging spectrosco...
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Vehicle Detection of Multi-source Remote Sensing Data Using Active Fine-tuning Network
Vehicle detection in remote sensing images has attracted increasing inte...
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Cross-Attention in Coupled Unmixing Nets for Unsupervised Hyperspectral Super-Resolution
The recent advancement of deep learning techniques has made great progre...
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X-ModalNet: A Semi-Supervised Deep Cross-Modal Network for Classification of Remote Sensing Data
This paper addresses the problem of semi-supervised transfer learning wi...
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Learning Convolutional Sparse Coding on Complex Domain for Interferometric Phase Restoration
Interferometric phase restoration has been investigated for decades and ...
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Feature Extraction for Hyperspectral Imagery: The Evolution from Shallow to Deep
Hyperspectral images provide detailed spectral information through hundr...
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Classification of Hyperspectral and LiDAR Data Using Coupled CNNs
In this paper, we propose an efficient and effective framework to fuse h...
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Invariant Attribute Profiles: A Spatial-Frequency Joint Feature Extractor for Hyperspectral Image Classification
Up to the present, an enormous number of advanced techniques have been d...
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Learning Shared Cross-modality Representation Using Multispectral-LiDAR and Hyperspectral Data
Due to the ever-growing diversity of the data source, multi-modality fea...
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MIMA: MAPPER-Induced Manifold Alignment for Semi-Supervised Fusion of Optical Image and Polarimetric SAR Data
Multi-modal data fusion has recently been shown promise in classificatio...
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Fourier-based Rotation-invariant Feature Boosting: An Efficient Framework for Geospatial Object Detection
Geospatial object detection of remote sensing imagery has been attractin...
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Cascaded Recurrent Neural Networks for Hyperspectral Image Classification
By considering the spectral signature as a sequence, recurrent neural ne...
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ORSIm Detector: A Novel Object Detection Framework in Optical Remote Sensing Imagery Using Spatial-Frequency Channel Features
With the rapid development of spaceborne imaging techniques, object dete...
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Learnable Manifold Alignment (LeMA) : A Semi-supervised Cross-modality Learning Framework for Land Cover and Land Use Classification
In this paper, we aim at tackling a general but interesting cross-modali...
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CoSpace: Common Subspace Learning from Hyperspectral-Multispectral Correspondences
With a large amount of open satellite multispectral imagery (e.g., Senti...
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An Augmented Linear Mixing Model to Address Spectral Variability for Hyperspectral Unmixing
Hyperspectral imagery collected from airborne or satellite sources inevi...
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Joint & Progressive Learning from High-Dimensional Data for Multi-Label Classification
Despite the fact that nonlinear subspace learning techniques (e.g. manif...
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