Deriving High Spatiotemporal Remote Sensing Images Using Deep Convolutional Network

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

(2017) Yancong Wei et al.   IEEE Geoscience and Remote Sensing Letters

Deep Fusion of Remote Sensing Data for Accurate Classification

(2017) Yushi Chen et al.   IEEE Geoscience and Remote Sensing Letters

Fully Convolutional Networks for Semantic Segmentation

(2017) Evan Shelhamer et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Multi-focus image fusion with a deep convolutional neural network

(2017) Yu Liu et al.   Information Fusion

A survey of deep neural network architectures and their applications

(2017) Weibo Liu et al.   NEUROCOMPUTING

Generating a series of fine spatial and temporal resolution land cover maps by fusing coarse spatial resolution remotely sensed images and fine spatial resolution land cover maps

(2017) Xiaodong Li et al.   REMOTE SENSING OF ENVIRONMENT

A New Spatial Attraction Model for Improving Subpixel Land Cover Classification

(2017) Lizhen Lu et al.   Remote Sensing

Deep Learning in Remote Sensing: A Comprehensive Review and List of Resources

(2017) Xiao Xiang Zhu et al.   IEEE Geoscience and Remote Sensing Magazine

Image Super-Resolution Using Deep Convolutional Networks

(2016) Chao Dong et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Remote sensing platforms and sensors: A survey

(2016) Charles Toth et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

A flexible spatiotemporal method for fusing satellite images with different resolutions

(2016) Xiaolin Zhu et al.   REMOTE SENSING OF ENVIRONMENT

Pansharpening by Convolutional Neural Networks

(2016) Giuseppe Masi et al.   Remote Sensing

Deep learning

(2015) Yann LeCun et al.   NATURE

Deep learning in neural networks: An overview

(2015) Jürgen Schmidhuber   NEURAL NETWORKS

Comparison of Spatiotemporal Fusion Models: A Review

(2015) Bin Chen et al.   Remote Sensing

Landsat-8: Science and product vision for terrestrial global change research

(2014) D.P. Roy et al.   REMOTE SENSING OF ENVIRONMENT

A spatial and temporal reflectance fusion model considering sensor observation differences

(2013) Huanfeng Shen et al.   INTERNATIONAL JOURNAL OF REMOTE SENSING

Web-service-based Monitoring and Analysis of Global Agricultural Drought

(2013) Meixia Deng et al.   PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING

Assessing the accuracy of blending Landsat–MODIS surface reflectances in two landscapes with contrasting spatial and temporal dynamics: A framework for algorithm selection

(2013) Irina V. Emelyanova et al.   REMOTE SENSING OF ENVIRONMENT

Spatiotemporal Reflectance Fusion via Sparse Representation

(2012) Bo Huang et al.   IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING

Earth Observation Sensor Web: An Overview

(2010) Liping Di et al.   IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

An enhanced spatial and temporal adaptive reflectance fusion model for complex heterogeneous regions

(2010) Xiaolin Zhu et al.   REMOTE SENSING OF ENVIRONMENT

Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling

(2009) Hoshin V. Gupta et al.   JOURNAL OF HYDROLOGY

A new data fusion model for high spatial- and temporal-resolution mapping of forest disturbance based on Landsat and MODIS

(2009) Thomas Hilker et al.   REMOTE SENSING OF ENVIRONMENT

Generation of dense time series synthetic Landsat data through data blending with MODIS using a spatial and temporal adaptive reflectance fusion model

(2009) Thomas Hilker et al.   REMOTE SENSING OF ENVIRONMENT

Unmixing-Based Landsat TM and MERIS FR Data Fusion

(2008) R. Zurita-Milla et al.   IEEE Geoscience and Remote Sensing Letters