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09/04/2023
Neural network-based emulation of interstellar medium models
The interpretation of observations of atomic and molecular tracers in th...
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08/18/2023
Image Processing and Machine Learning for Hyperspectral Unmixing: An Overview and the HySUPP Python Package
Spectral pixels are often a mixture of the pure spectra of the materials...
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08/09/2023
SUnAA: Sparse Unmixing using Archetypal Analysis
This paper introduces a new sparse unmixing technique using archetypal a...
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10/21/2022
Self-Supervised Pretraining on Satellite Imagery: a Case Study on Label-Efficient Vehicle Detection
In defense-related remote sensing applications, such as vehicle detectio...
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10/13/2022
Evaluating the Label Efficiency of Contrastive Self-Supervised Learning for Multi-Resolution Satellite Imagery
The application of deep neural networks to remote sensing imagery is oft...
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09/22/2022
Entropic Descent Archetypal Analysis for Blind Hyperspectral Unmixing
In this paper, we introduce a new algorithm based on archetypal analysis...
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06/24/2022
Self Supervised Learning for Few Shot Hyperspectral Image Classification
Deep learning has proven to be a very effective approach for Hyperspectr...
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04/18/2022
Optical Remote Sensing Image Understanding with Weak Supervision: Concepts, Methods, and Perspectives
In recent years, supervised learning has been widely used in various tas...
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12/04/2021
A Triple-Double Convolutional Neural Network for Panchromatic Sharpening
Pansharpening refers to the fusion of a panchromatic image with a high s...
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11/26/2021
Geometric Multimodal Deep Learning with Multi-Scaled Graph Wavelet Convolutional Network
Multimodal data provide complementary information of a natural phenomeno...
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11/18/2021
A Trainable Spectral-Spatial Sparse Coding Model for Hyperspectral Image Restoration
Hyperspectral imaging offers new perspectives for diverse applications, ...
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08/18/2021
Multi-patch Feature Pyramid Network for Weakly Supervised Object Detection in Optical Remote Sensing Images
Object detection is a challenging task in remote sensing because objects...
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07/27/2021
Unsupervised Outlier Detection using Memory and Contrastive Learning
Outlier detection is one of the most important processes taken to create...
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06/02/2021
Rotation Equivariant Feature Image Pyramid Network for Object Detection in Optical Remote Sensing Imagery
Over the last few years, there has been substantial progress in object d...
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05/12/2021
Cross-Modal and Multimodal Data Analysis Based on Functional Mapping of Spectral Descriptors and Manifold Regularization
Multimodal manifold modeling methods extend the spectral geometry-aware ...
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05/10/2021
An Attention-Fused Network for Semantic Segmentation of Very-High-Resolution Remote Sensing Imagery
Semantic segmentation is an essential part of deep learning. In recent y...
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03/30/2021
Using Low-rank Representation of Abundance Maps and Nonnegative Tensor Factorization for Hyperspectral Nonlinear Unmixing
Tensor-based methods have been widely studied to attack inverse problems...
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08/06/2020
Graph Convolutional Networks for Hyperspectral Image Classification
Convolutional neural networks (CNNs) have been attracting increasing att...
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07/28/2020
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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07/28/2020
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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07/17/2020
Spatial-Spectral Manifold Embedding of Hyperspectral Data
In recent years, hyperspectral imaging, also known as imaging spectrosco...
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07/10/2020
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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06/24/2020
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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05/29/2020
Hyperspectral Image Super-resolution via Deep Spatio-spectral Convolutional Neural Networks
Hyperspectral images are of crucial importance in order to better unders...
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04/02/2020
Graph-based fusion for change detection in multi-spectral images
In this paper we address the problem of change detection in multi-spectr...
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03/05/2020
Feature Extraction for Hyperspectral Imagery: The Evolution from Shallow to Deep
Hyperspectral images provide detailed spectral information through hundr...
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12/18/2019
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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12/18/2019
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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06/04/2019
An Introduction to Deep Morphological Networks
The recent impressive results of deep learning-based methods on computer...
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05/27/2019
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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01/23/2019
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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01/09/2019
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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12/30/2018
CoSpace: Common Subspace Learning from Hyperspectral-Multispectral Correspondences
With a large amount of open satellite multispectral imagery (e.g., Senti...
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10/29/2018
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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04/11/2018
Dynamic Multi-Scale Semantic Segmentation based on Dilated Convolutional Networks
Semantic segmentation requires methods capable of learning high-level fe...
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11/13/2017
Conditional Random Field and Deep Feature Learning for Hyperspectral Image Segmentation
Image segmentation is considered to be one of the critical tasks in hype...
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02/03/2016
A Framework for Fast Image Deconvolution with Incomplete Observations
In image deconvolution problems, the diagonalization of the underlying o...
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10/14/2015
Dynamical spectral unmixing of multitemporal hyperspectral images
In this paper, we consider the problem of unmixing a time series of hype...
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04/17/2015
Hyperspectral pansharpening: a review
Pansharpening aims at fusing a panchromatic image with a multispectral o...
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11/14/2014
A convex formulation for hyperspectral image superresolution via subspace-based regularization
Hyperspectral remote sensing images (HSIs) usually have high spectral re...
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03/31/2014
Hyperspectral image superresolution: An edge-preserving convex formulation
Hyperspectral remote sensing images (HSIs) are characterized by having a...
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02/28/2012