Deep learning in remote sensing applications: A meta-analysis and review (2019-06-01T00:00:00.000000Z)

TL;DR

This review covers nearly every application and technology in the field of remote sensing, ranging from preprocessing to mapping, and a conclusion regarding the current state-of-the art methods, a critical conclusion on open challenges, and directions for future research are presented.

Authors

Lei Ma

1 papers

Yu Liu

1 papers

Xueliang Zhang

1 papers

Yuanxin Ye

1 papers

Gaofei Yin

1 papers

Brian Alan Johnson

1 papers

TL;DR

Authors

References155 items

From Google Maps to a Fine-Grained Catalog of Street trees

Aligning and Updating Cadaster Maps with Aerial Images by Multi-task, Multi-resolution Deep Learning

A deep learning framework for remote sensing image registration

Pan-sharpening via deep metric learning

Multi-scale object detection in remote sensing imagery with convolutional neural networks

Deep learning for remote sensing image classification: A survey

An object-based convolutional neural network (OCNN) for urban land use classification

Mining Hard Negative Samples for SAR-Optical Image Matching Using Generative Adversarial Networks

Multimodal Image Alignment Through a Multiscale Chain of Neural Networks with Application to Remote Sensing

Urban land-use mapping using a deep convolutional neural network with high spatial resolution multispectral remote sensing imagery

Fusion of images and point clouds for the semantic segmentation of large-scale 3D scenes based on deep learning

Learning Transferable Deep Models for Land-Use Classification with High-Resolution Remote Sensing Images

A light and faster regional convolutional neural network for object detection in optical remote sensing images

Deep learning for pixel-level image fusion: Recent advances and future prospects

Exploring geo-tagged photos for land cover validation with deep learning

Detecting Mammals in UAV Images: Best Practices to address a substantially Imbalanced Dataset with Deep Learning

Region-Wise Deep Feature Representation for Remote Sensing Images

A high-performance and in-season classification system of field-level crop types using time-series Landsat data and a machine learning approach

Hyperspectral and Multispectral Image Fusion via Deep Two-Branches Convolutional Neural Network

Using convolutional neural network to identify irregular segmentation objects from very high-resolution remote sensing imagery

Deep convolutional neural network training enrichment using multi-view object-based analysis of Unmanned Aerial systems imagery for wetlands classification

3-D Deep Learning Approach for Remote Sensing Image Classification

Optimization of OpenStreetMap Building Footprints Based on Semantic Information of Oblique UAV Images

One-Two-One Networks for Compression Artifacts Reduction in Remote Sensing

Multi-class geospatial object detection based on a position-sensitive balancing framework for high spatial resolution remote sensing imagery

Two-Stream Deep Architecture for Hyperspectral Image Classification

Exploring the Potential of Conditional Adversarial Networks for Optical and SAR Image Matching

Symmetrical Dense-Shortcut Deep Fully Convolutional Networks for Semantic Segmentation of Very-High-Resolution Remote Sensing Images

Long-Term Annual Mapping of Four Cities on Different Continents by Applying a Deep Information Learning Method to Landsat Data

Land cover mapping at very high resolution with rotation equivariant CNNs: towards small yet accurate models

Pixel-Wise Classification Method for High Resolution Remote Sensing Imagery Using Deep Neural Networks

Super-Resolution of Sentinel-2 Images: Learning a Globally Applicable Deep Neural Network

Remote Sensing Image Fusion With Deep Convolutional Neural Network

Generative Adversarial Networks for Hyperspectral Image Classification

IMG2DSM: Height Simulation From Single Imagery Using Conditional Generative Adversarial Net

Matching of Remote Sensing Images with Complex Background Variations via Siamese Convolutional Neural Network

Deep Hyperspectral Image Sharpening

When Low Rank Representation Based Hyperspectral Imagery Classification Meets Segmented Stacked Denoising Auto-Encoder Based Spatial-Spectral Feature

Semisupervised Hyperspectral Image Classification Based on Generative Adversarial Networks

Multisource Remote Sensing Data Classification Based on Convolutional Neural Network

Deep Recurrent Neural Networks for Winter Vegetation Quality Mapping via Multitemporal SAR Sentinel-1

Identifying Corresponding Patches in SAR and Optical Images With a Pseudo-Siamese CNN

Building Extraction in Very High Resolution Remote Sensing Imagery Using Deep Learning and Guided Filters

End-to-End Airplane Detection Using Transfer Learning in Remote Sensing Images

When Deep Learning Meets Metric Learning: Remote Sensing Image Scene Classification via Learning Discriminative CNNs

Semantic Segmentation of Aerial Images With Shuffling Convolutional Neural Networks

A Multiscale and Multidepth Convolutional Neural Network for Remote Sensing Imagery Pan-Sharpening

Translation-aware semantic segmentation via conditional least-square generative adversarial networks

GANGs: Generative Adversarial Network Games

A semi-supervised generative framework with deep learning features for high-resolution remote sensing image scene classification

Beyond RGB: Very High Resolution Urban Remote Sensing With Multimodal Deep Networks

MugNet: Deep learning for hyperspectral image classification using limited samples

A patch-based convolutional neural network for remote sensing image classification

Multilayer Projective Dictionary Pair Learning and Sparse Autoencoder for PolSAR Image Classification

Deep learning in remote sensing: a review

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

Comprehensive survey of deep learning in remote sensing: theories, tools, and challenges for the community

Target-Adaptive CNN-Based Pansharpening

Stacked Sparse Autoencoder Modeling Using the Synergy of Airborne LiDAR and Satellite Optical and SAR Data to Map Forest Above-Ground Biomass

Multiview Canonical Correlation Analysis Networks for Remote Sensing Image Recognition

Spectral–spatial feature learning for hyperspectral imagery classification using deep stacked sparse autoencoder

Surface Water Mapping by Deep Learning

A Novel Methodology to Label Urban Remote Sensing Images Based on Location-Based Social Media Photos

Unsupervised Deep Feature Learning for Urban Village Detection from High-Resolution Remote Sensing Images

A review of supervised object-based land-cover image classification

Estimating Ground‐Level PM2.5 by Fusing Satellite and Station Observations: A Geo‐Intelligent Deep Learning Approach

Feature learning and change feature classification based on deep learning for ternary change detection in SAR images

PatternNet: A Benchmark Dataset for Performance Evaluation of Remote Sensing Image Retrieval

Exploiting Deep Matching and SAR Data for the Geo-Localization Accuracy Improvement of Optical Satellite Images

Hourglass-ShapeNetwork Based Semantic Segmentation for High Resolution Aerial Imagery

Boosting the Accuracy of Multispectral Image Pansharpening by Learning a Deep Residual Network

Learning Dual Multi-Scale Manifold Ranking for Semantic Segmentation of High-Resolution Images

Deep learning in remote sensing scene classification: a data augmentation enhanced convolutional neural network framework

Gated Convolutional Neural Network for Semantic Segmentation in High-Resolution Images

Cascaded Recurrent Neural Networks for Hyperspectral Image Classification

Social Media: New Perspectives to Improve Remote Sensing for Emergency Response

Land Cover Classification via Multitemporal Spatial Data by Deep Recurrent Neural Networks