109 results on '"Sveinsson, Johannes R."'
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2. Unsupervised Sentinel-2 Image Fusion Using a Deep Unrolling Method
3. Hyperspectral Super-Resolution by Unsupervised Convolutional Neural Network and Sure
4. Deep Sparse and Low-Rank Prior for Hyperspectral Image Denoising
5. Fusing Sentinel-2 and Landsat 8 Satellite Images Using a Model-Based Method
6. Semi-Supervised Mixtures of Factor Analyzers Feature Extraction for Hyperspectral Images
7. Hyperspectral Image Denoising Using Spectral-Spatial Transform-Based Sparse and Low-Rank Representations
8. Synthetic Hyperspectral Images With Controllable Spectral Variability and Ground Truth
9. Blind Hyperspectral Unmixing Using Autoencoders: A Critical Comparison
10. Deep SURE for Unsupervised Remote Sensing Image Fusion
11. Sharpening the 20 M Bands of SENTINEL-2 Image Using an Unsupervised Convolutional Neural Network
12. Wavelet-Based Block Low-Rank Representations for Hyperspectral Denoising
13. Fusing Sentinel-2 Satellite Images and Aerial RGB Images
14. Tuning Parameter Selection for Sentinel-2 Sharpening Using Wald's Protocol
15. Non-Local Means Low-Rank Approximation for Hyperspectral Denoising
16. A Comparison of Optimized Sentinel-2 Super-Resolution Methods Using Wald’s Protocol and Bayesian Optimization
17. Hyperspectral Image Denoising Using SURE-Based Unsupervised Convolutional Neural Networks
18. Convolutional Autoencoder for Spectral–Spatial Hyperspectral Unmixing
19. Sentinel-2 Sharpening Using a Single Unsupervised Convolutional Neural Network With MTF-Based Degradation Model
20. Classifying Remote Sensing Data with Support Vector Machines and Imbalanced Training Data
21. Ensemble Strategies for Classifying Hyperspectral Remote Sensing Data
22. Spectrally Consistent Pansharpening
23. Sure Based Convolutional Neural Networks for Hyperspectral Image Denoising
24. Hyperspectral Images Denoising Based on Mixtures of Factor Analyzers
25. Creating RGB Images from Hyperspectral Images Using a Color Matching Function
26. Local Spatial-Spectral Correlation Based Mixtures of Factor Analyzers for Hyperspectral Denoising
27. Zero-Shot Sentinel-2 Sharpening Using a Symmetric Skipped Connection Convolutional Neural Network
28. Unsupervised and Supervised Feature Extraction Methods for Hyperspectral Images Based on Mixtures of Factor Analyzers
29. Model-Based Reduced-Rank Pansharpening
30. Boosting, Bagging, and Consensus Based Classification of Multisource Remote Sensing Data
31. Consensus Based Classification of Multisource Remote Sensing Data
32. Feature Extraction for Neural Network Classifiers
33. Sentinel-2 Sharpening Using a Reduced-Rank Method
34. (Semi-) Supervised Mixtures of Factor Analyzers and Deep Mixtures of Factor Analyzers Dimensionality Reduction Algorithms For Hyperspectral Images Classification
35. Mixtures of Factor Analyzers and Deep Mixtures of Factor Analyzers Dimensionality Reduction Algorithms For Hyperspectral Images Classification
36. Optimal Component Substitution and Multi-Resolution Analysis Pansharpening Methods Using a Convolutional Neural Network
37. Convolutional Autoencoder for Spatial-Spectral Hyperspectral Unmixing
38. Multitask Learning for Spatial-Spectral Hyperspectral Unmixing
39. Weighted Blind ℓqHyperspectral Unmixing
40. Spectral-Spatial Hyperspectral Unmixing Using Multitask Learning
41. Parameter Estimation For Blind lq Hyperspectral Unmixing Using Bayesian Optimization
42. Single Sensor Image Fusion Using a Deep Residual Network
43. Single Sensor Image Fusion Using A Deep Convolutional Generative Adversarial Network
44. Hyperspectral Unmixing Using a Neural Network Autoencoder
45. Sparse Distributed Multitemporal Hyperspectral Unmixing
46. Fast multitemporal hyperspectral unmixing
47. Sparse and low rank hyperspectral unmixing
48. Neural network hyperspectral unmixing with spectral information divergence objective
49. Multispectral and Hyperspectral Image Fusion Using a 3-D-Convolutional Neural Network
50. Hyperspectral Feature Extraction Using Total Variation Component Analysis
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