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Review of pixel-level remote sensing image fusion based on deep learning

https://doi.org/10.1016/j.inffus.2022.09.008
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Context-Adaptive Pansharpening Based on Image Segmentation
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Target-Adaptive CNN-Based Pansharpening
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HAM-MFN: Hyperspectral and Multispectral Image Multiscale Fusion Network With RAP Loss
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Band-Independent Encoder–Decoder Network for Pan-Sharpening of Remote Sensing Images
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Coupled Convolutional Neural Network With Adaptive Response Function Learning for Unsupervised Hyperspectral Super Resolution
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Unsupervised Pansharpening Based on Self-Attention Mechanism
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Super-Resolution-Guided Progressive Pansharpening Based on a Deep Convolutional Neural Network
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Two Stages Pan-Sharpening Details Injection Approach Based on Very Deep Residual Networks
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Improving Satellite Image Fusion via Generative Adversarial Training
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Detail Injection-Based Deep Convolutional Neural Networks for Pansharpening
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PSGAN: A Generative Adversarial Network for Remote Sensing Image Pan-Sharpening
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SC-PNN: Saliency Cascade Convolutional Neural Network for Pansharpening
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Multibranch Feature Extraction and Feature Multiplexing Network for Pansharpening
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VP-Net: An Interpretable Deep Network for Variational Pansharpening
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A Dual-Path Fusion Network for Pan-Sharpening
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Dual-Stream Convolutional Neural Network With Residual Information Enhancement for Pansharpening
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Multistage Dual-Attention Guided Fusion Network for Hyperspectral Pansharpening
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PanCSC-Net: A Model-Driven Deep Unfolding Method for Pansharpening
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Category-Wise Fusion and Enhancement Learning for Multimodal Remote Sensing Image Semantic Segmentation
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Hyperspectral Image Super-Resolution via Non-Negative Structured Sparse Representation
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FusionNet: An Unsupervised Convolutional Variational Network for Hyperspectral and Multispectral Image Fusion
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Deep Hierarchical Vision Transformer for Hyperspectral and LiDAR Data Classification
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Deep Multiscale Detail Networks for Multiband Spectral Image Sharpening
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Deep Blind Hyperspectral Image Super-Resolution
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Spectral Response Function-Guided Deep Optimization-Driven Network for Spectral Super-Resolution
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Image Super-Resolution Using Deep Convolutional Networks
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Fast and Accurate Image Super-Resolution with Deep Laplacian Pyramid Networks
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Squeeze-and-Excitation Networks
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Multispectral and Panchromatic Data Fusion Assessment Without Reference
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Snow Cover Mapping for Mountainous Areas by Fusion of MODIS L1B and Geographic Data Based on Stacked Denoising Auto-Encoders
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A CNN-Based Fusion Method for Feature Extraction from Sentinel Data
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Sentinel-2 Image Fusion Using a Deep Residual Network
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Deep Self-Learning Network for Adaptive Pansharpening
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Fast Super-Resolution of 20 m Sentinel-2 Bands Using Convolutional Neural Networks
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Spatiotemporal Fusion of Satellite Images via Very Deep Convolutional Networks
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Improved SRGAN for Remote Sensing Image Super-Resolution Across Locations and Sensors
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Two-Path Network with Feedback Connections for Pan-Sharpening in Remote Sensing
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Multi-Image Super Resolution of Remotely Sensed Images Using Residual Attention Deep Neural Networks
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PlanetScope Radiometric Normalization and Sentinel-2 Super-Resolution (2.5 m): A Straightforward Spectral-Spatial Fusion of Multi-Satellite Multi-Sensor Images Using Residual Convolutional Neural Networks
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Super-Resolution of Sentinel-2 Imagery Using Generative Adversarial Networks
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MDECNN: A Multiscale Perception Dense Encoding Convolutional Neural Network for Multispectral Pan-Sharpening
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Spatiotemporal Fusion of Formosat-2 and Landsat-8 Satellite Images: A Comparison of “Super Resolution-Then-Blend” and “Blend-Then-Super Resolution” Approaches
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A Hybrid Deep Learning-Based Spatiotemporal Fusion Method for Combining Satellite Images with Different Resolutions
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MSDRN: Pansharpening of Multispectral Images via Multi-Scale Deep Residual Network
inferredcites →https://doi.org/10.3390/rs13101962openalex-snapshot
Hybrid Attention Based Residual Network for Pansharpening
inferredcites →https://doi.org/10.3390/rs13112218openalex-snapshot
MDCwFB: A Multilevel Dense Connection Network with Feedback Connections for Pansharpening
inferredcites →https://doi.org/10.3390/rs13142800openalex-snapshot
Detail Information Prior Net for Remote Sensing Image Pansharpening
inferredcites →https://doi.org/10.3390/rs13183724openalex-snapshot
MSNet: A Multi-Stream Fusion Network for Remote Sensing Spatiotemporal Fusion Based on Transformer and Convolution
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A Robust Hybrid Deep Learning Model for Spatiotemporal Image Fusion
inferredcites →https://doi.org/10.3390/rs8030215openalex-snapshot
Downscaling of MODIS One Kilometer Evapotranspiration Using Landsat-8 Data and Machine Learning Approaches
inferredcites →https://doi.org/10.3390/rs8070594openalex-snapshot
Pansharpening by Convolutional Neural Networks
inferredcites →https://doi.org/10.3390/rs9121310openalex-snapshot
A Bayesian Data Fusion Approach to Spatio-Temporal Fusion of Remotely Sensed Images
inferredcites →https://doi.org/10.3390/s150924002openalex-snapshot
Generating Daily Synthetic Landsat Imagery by Combining Landsat and MODIS Data
inferredcites →https://doi.org/10.3390/s18124330openalex-snapshot
Variational Pansharpening for Hyperspectral Imagery Constrained by Spectral Shape and Gram–Schmidt Transformation
inferredcites →https://doi.org/10.3390/sym12061056openalex-snapshot
Cloud Detection for Satellite Imagery Using Attention-Based U-Net Convolutional Neural Network
inferredcites →https://doi.org/10.48550/arxiv.1409.1556openalex-snapshot
Very Deep Convolutional Networks for Large-Scale Image Recognition
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An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
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THE SEN1-2 DATASET FOR DEEP LEARNING IN SAR-OPTICAL DATA FUSION
inferredcites →https://doi.org/10.5194/isprs-annals-iv-1-5-2018openalex-snapshot
SAR TO OPTICAL IMAGE SYNTHESIS FOR CLOUD REMOVAL WITH GENERATIVE ADVERSARIAL NETWORKS
inferredcites →https://doi.org/10.5194/isprs-annals-iv-2-w7-153-2019openalex-snapshot
SEN12MS – A CURATED DATASET OF GEOREFERENCED MULTI-SPECTRAL SENTINEL-1/2 IMAGERY FOR DEEP LEARNING AND DATA FUSION
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Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Lightweight Progressive Multilevel Feature Collaborative Network for Remote Sensing Image Salient Object Detection
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Multiscale Sparse Cross-Attention Network for Remote Sensing Scene Classification
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EXP-PnP: General Extended Model for Detail-Injected Pan-Sharpening With Plug-and-Play Residual Optimization
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Sparse-to-Dense Prediction of Ocean Subsurface Temperature Using Multilevel Spatiotemporal Information Fusion
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HTMP: Triple-Scale Multilevel Network With Hessian Spatial Loss for Pansharpening
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Spatial–Spectral Dual Guided Network With Joint Attention for Pansharpening
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FG-GAN: Frequency-Guided Generative Adversarial Networks for Unsupervised Pansharpening
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MSDCN-LSTF: A Multiscale and Multidimensional Collaboration Network for Land Surface Temperature Spatiotemporal Fusion Based on Transformer and Convolution
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ArtFusion: An Arbitrary-Reference Spatiotemporal Fusion Model for Seamless Remote Sensing Image Reconstruction
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Global Semantic Prototype-Guided Contrastive Learning for Few-Shot Joint Classification of MS and PAN
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Correlation-Guided Discriminative Cross-Modality Features Network for Infrared and Visible Image Fusion
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F2Fusion: Frequency Feature Fusion Network for Infrared and Visible Image via Contourlet Transform and Mamba-UNet
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A Wild Terrain Segmentation Network for Navigable Areas via Entropy-Guided Global Sparsification and Dynamic Attention Fusion
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Image Fusion Based on Prior Information
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Infrared and visible image fusion: A survey of Current Research Status
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Unmanned Aerial Vehicle (UAV) Based Disaster Detection and Crowd Sensing Using Deep Learning Models
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Image Fusion in Remote Sensing: An Overview and Meta-Analysis
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OTPNet: ODE-inspired Tuning-free Proximal Network for Remote Sensing Image Fusion
inferred← citeshttps://doi.org/10.2139/ssrn.5674746openalex-snapshot
MuSS: A Multimodal Satellite Service for Unsupervised Multi-Class Land Cover Classification
inferred← citeshttps://doi.org/10.2139/ssrn.6904948openalex-snapshot
Intersection-Oriented Multimodal Object Detection via Self-Adaptive Weighted Fusion for Intelligent Vehicle Applications
inferred← citeshttps://doi.org/10.22630/mgv.2023.32.1.4openalex-snapshot
Riesz-Laplace Wavelet Transform and PCNN Based Image Fusion
inferred← citeshttps://doi.org/10.3389/frsen.2023.1136289openalex-snapshot
Exploiting hyperspectral and multispectral images in the detection of tree species: A review
inferred← citeshttps://doi.org/10.3390/agronomy13102608openalex-snapshot
Adaptability Evaluation of the Spatiotemporal Fusion Model in the Summer Maize Planting Area of the Southeast Loess Plateau
inferred← citeshttps://doi.org/10.3390/app15126649openalex-snapshot
A Bidirectional Cross Spatiotemporal Fusion Network with Spectral Restoration for Remote Sensing Imagery
inferred← citeshttps://doi.org/10.3390/f15010197openalex-snapshot
Green Space Reverse Pixel Shuffle Network: Urban Green Space Segmentation Using Reverse Pixel Shuffle for Down-Sampling from High-Resolution Remote Sensing Images
inferred← citeshttps://doi.org/10.3390/rs16111833openalex-snapshot
Fast Fusion of Sentinel-2 and Sentinel-3 Time Series over Rangelands
inferred← citeshttps://doi.org/10.3390/rs16162941openalex-snapshot
Pansharpening Based on Multimodal Texture Correction and Adaptive Edge Detail Fusion
inferred← citeshttps://doi.org/10.3390/rs17050927openalex-snapshot
Adapting Cross-Sensor High-Resolution Remote Sensing Imagery for Land Use Classification
inferred← citeshttps://doi.org/10.3390/rs17061071openalex-snapshot
A Dual-Branch Network of Strip Convolution and Swin Transformer for Multimodal Remote Sensing Image Registration
inferred← citeshttps://doi.org/10.3390/rs17071131openalex-snapshot
An Approach for Multi-Source Land Use and Land Cover Data Fusion Considering Spatial Correlations
inferred← citeshttps://doi.org/10.3390/rs17091510openalex-snapshot
Spatiotemporal Fusion of Multi-Temporal MODIS and Landsat-8/9 Imagery for Enhanced Daily 30 m NDVI Reconstruction: A Case Study of the Shiyang River Basin Cropland (2022)
inferred← citeshttps://doi.org/10.3390/rs17121973openalex-snapshot
Hyperspectral and Multispectral Remote Sensing Image Fusion Based on a Retractable Spatial–Spectral Transformer Network
inferred← citeshttps://doi.org/10.3390/rs18020238openalex-snapshot
Deep-Learning Spatial and Temporal Fusion Model for Land Surface Temperature Based on a Spatially Adaptive Feature and Temperature-Adaptive Correction Module
inferred← citeshttps://doi.org/10.3390/rs18020289openalex-snapshot
Deep Learning for Spatio-Temporal Fusion in Land Surface Temperature Estimation: A Comprehensive Survey, Experimental Analysis, and Future Trends
inferred← citeshttps://doi.org/10.3390/rs18030511openalex-snapshot
Text2AIRS: Fine-Grained Airplane Image Generation in Remote Sensing from Nature Language
inferred← citeshttps://doi.org/10.3390/rs18040570openalex-snapshot
Mapping Forest Aboveground Carbon Storage by Integrating Multi-Source Optical and Multi-Temporal Sentinel-1 SAR Data in Mixed Broadleaf–Coniferous Forests
inferred← citeshttps://doi.org/10.3390/rs18101536openalex-snapshot
Improving Forest Aboveground Biomass Estimation Accuracy via Optical and SAR Data Fusion Using Deep Learning Algorithms
inferred← citeshttps://doi.org/10.3390/rs18142299openalex-snapshot
PanDiM: A Diffusion Mamba Network for High-Fidelity Pansharpening
inferred← citeshttps://doi.org/10.3390/smartcities6050134openalex-snapshot
A Comparative Analysis of Multi-Label Deep Learning Classifiers for Real-Time Vehicle Detection to Support Intelligent Transportation Systems
inferred← citeshttps://doi.org/10.3788/gzxb20235211.1110001openalex-snapshot
基于改进Swin transformer的遥感图像融合方法
inferred← citeshttps://doi.org/10.48084/etasr.10622openalex-snapshot
An Improved Medical Image Fusion for Efficient Diagnostic Imaging Using Deep Learning and Gradient-Based Quality Assessment
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