| When Deep Learning Meets Metric Learning: Remote Sensing Image Scene Classification via Learning Discriminative CNNs |
149 |
| Spectral-Spatial Residual Network for Hyperspectral Image Classification: A 3-D Deep Learning Framework |
114 |
| Deep Learning for Hyperspectral Image Classification: An Overview |
96 |
| Scene Classification With Recurrent Attention of VHR Remote Sensing Images |
71 |
| Hyperspectral Image Classification With Deep Feature Fusion Network |
65 |
| Generative Adversarial Networks for Hyperspectral Image Classification |
64 |
| Recent Advances on Spectral-Spatial Hyperspectral Image Classification: An Overview and New Guidelines |
61 |
| Rotation-Insensitive and Context-Augmented Object Detection in Remote Sensing Images |
50 |
| Exploring Hierarchical Convolutional Features for Hyperspectral Image Classification |
49 |
| Learning Spectral-Spatial-Temporal Features via a Recurrent Convolutional Neural Network for Change Detection in Multispectral Imagery |
47 |
| GETNET: A General End-to-End 2-D CNN Framework for Hyperspectral Image Change Detection |
44 |
| Deep-Learning Schemes for Full-Wave Nonlinear Inverse Scattering Problems |
43 |
| Hyperspectral Image Denoising Employing a Spatial-Spectral Deep Residual Convolutional Neural Network |
41 |
| Missing Data Reconstruction in Remote Sensing Image With a Unified Spatial-Temporal-Spectral Deep Convolutional Neural Network |
40 |
| Deep Pyramidal Residual Networks for Spectral-Spatial Hyperspectral Image Classification |
39 |
| Fully Convolutional Networks for Multisource Building Extraction From an Open Aerial and Satellite Imagery Data Set |
39 |
| Guided Locality Preserving Feature Matching for Remote Sensing Image Registration |
39 |
| Exploring Models and Data for Remote Sensing Image Caption Generation |
39 |
| Hyperspectral Image Classification With Deep Learning Models |
38 |
| Edge-Enhanced GAN for Remote Sensing Image Superresolution |
38 |
| Large-Scale Remote Sensing Image Retrieval by Deep Hashing Neural Networks |
38 |
| Multisource Remote Sensing Data Classification Based on Convolutional Neural Network |
37 |
| SuperPCA: A Superpixelwise PCA Approach for Unsupervised Feature Extraction of Hyperspectral Imagery |
37 |
| Capsule Networks for Hyperspectral Image Classification |
36 |
| Cascaded Recurrent Neural Networks for Hyperspectral Image Classification |
36 |
| Learning Compact and Discriminative Stacked Autoencoder for Hyperspectral Image Classification |
36 |
| Spectral-Spatial Unified Networks for Hyperspectral Image Classification |
36 |
| 3-D Deep Learning Approach for Remote Sensing Image Classification |
35 |
| CoSpace: Common Subspace Learning From Hyperspectral-Multispectral Correspondences |
35 |
| Remote Sensing Scene Classification Using Multilayer Stacked Covariance Pooling |
34 |
| Optimal Clustering Framework for Hyperspectral Band Selection |
30 |
| Ice Cloud Properties From Himawari-8/AHI Next-Generation Geostationary Satellite: Capability of the AHI to Monitor the DC Cloud Generation Process |
30 |
| Toward Global Soil Moisture Monitoring With Sentinel-1: Harnessing Assets and Overcoming Obstacles |
29 |
| Cloud Detection in Remote Sensing Images Based on Multiscale Features-Convolutional Neural Network |
29 |
| A New Spatial-Spectral Feature Extraction Method for Hyperspectral Images Using Local Covariance Matrix Representation |
28 |
| Supervised Deep Feature Extraction for Hyperspectral Image Classification |
28 |
| SAR Automatic Target Recognition Based on Multiview Deep Learning Framework |
28 |
| Unsupervised Spectral-Spatial Feature Learning via Deep Residual Conv-Deconv Network for Hyperspectral Image Classification |
28 |
| Feature Extraction With Multiscale Covariance Maps for Hyperspectral Image Classification |
28 |
| Locality and Structure Regularized Low Rank Representation for Hyperspectral Image Classification |
27 |
| An Operational Land Surface Temperature Product for Landsat Thermal Data: Methodology and Validation |
27 |
| Target-Adaptive CNN-Based Pansharpening |
26 |
| Graph-Regularized Fast and Robust Principal Component Analysis for Hyperspectral Band Selection |
26 |
| Learning Source-Invariant Deep Hashing Convolutional Neural Networks for Cross-Source Remote Sensing Image Retrieval |
25 |
| HSI-DeNet: Hyperspectral Image Restoration via Convolutional Neural Network |
25 |
| Unsupervised Deep Change Vector Analysis for Multiple-Change Detection in VHR Images |
24 |
| Active Learning With Convolutional Neural Networks for Hyperspectral Image Classification Using a New Bayesian Approach |
24 |
| Hypergraph p-Laplacian Regularization for Remotely Sensed Image Recognition |
24 |
| Active Transfer Learning Network: A Unified Deep Joint Spectral-Spatial Feature Learning Model for Hyperspectral Image Classification |
24 |
| Multilabel Remote Sensing Image Retrieval Using a Semisupervised Graph-Theoretic Method |
24 |
