PUBLICACIÓN

Generative Models for Hyperspectral Imaging Processing

ACCEDER A LA PUBLICACIÓN: Scopus Orcid

Carlos Cañada-Rostro; Pan Zheng; María B. García-Flores; Mercedes E. Paoletti

2026

CITAS

0

DOI

10.1007/978-981-95-2038-1_4

EID

2-s2.0-105036213469

ISSN

2191-6586

EISSN

2191-6594

AUTORES DE LA UEX

Mercedes Eugenia Paoletti Ávila

OTRAS PUBLICACIONES DE INTERÉS

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Advances In Deep Neural Architectures For Hyperspectral Image Analysis
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Hyperspectral Anomaly Detection With Relaxed Collaborative Representation
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Generative Adversarial Minority Oversampling For Spectral-Spatial Hyperspectral Image Classification
Separable Attention Network In Single- And Mixed-Precision Floating Point For Land-Cover Classification Of Remote Sensing Images
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Gpu-Friendly Neural Networks For Remote Sensing Scene Classification
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Heterogeneous Model Parallelism For Deep Neural Networks
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Endmember Estimation With Maximum Distance Analysis
Multiple Incremental Kernel Convolution For Land Cover Classification Of Remotely Sensed Images
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Multiple Incremental Kernel Convolution For Land Cover Classification Of Remotely Sensed Images
Adapting Kernels For Hyperspectral Image Classification
Multiple Incremental Kernel Convolution For Land Cover Classification Of Remotely Sensed Images
Adapting Kernels For Hyperspectral Image Classification
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Adapting Kernels For Hyperspectral Image Classification
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Sicodef² Net: Siamese Convolution Deconvolution Feature Fusion Network For One-Shot Classification
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Analysis Of Remotely Sensed Images Through Social Media
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Analysis Of Remotely Sensed Images Through Social Media
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Cloud Implementation Of Multinomial Logistic Regression For Uav Hyperspectral Images
Angulargrad: A New Optimization Technique For Angular Convergence Of Convolutional Neural Networks
Cloud Implementation Of Multinomial Logistic Regression For Uav Hyperspectral Images
Training Deep Neural Networks: A Static Load Balancing Approach
Cloud Implementation Of Multinomial Logistic Regression For Uav Hyperspectral Images
Training Deep Neural Networks: A Static Load Balancing Approach
Scalable Recurrent Neural Network For Hyperspectral Image Classification
Training Deep Neural Networks: A Static Load Balancing Approach
Scalable Recurrent Neural Network For Hyperspectral Image Classification
Training Capsnets Via Active Learning For Hyperspectral Image Classification
Scalable Recurrent Neural Network For Hyperspectral Image Classification
Training Capsnets Via Active Learning For Hyperspectral Image Classification
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Training Capsnets Via Active Learning For Hyperspectral Image Classification
Neighboring Region Dropout For Hyperspectral Image Classification
A New Gpu Implementation Of Support Vector Machines For Fast Hyperspectral Image Classification
Neighboring Region Dropout For Hyperspectral Image Classification
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A Single Model Cnn For Hyperspectral Image Denoising
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A Single Model Cnn For Hyperspectral Image Denoising
Neural Ordinary Differential Equations For Hyperspectral Image Classification
A Single Model Cnn For Hyperspectral Image Denoising
Neural Ordinary Differential Equations For Hyperspectral Image Classification
Inference In Supervised Spectral Classifiers For On-Board Hyperspectral Imaging: An Overview
Neural Ordinary Differential Equations For Hyperspectral Image Classification
Inference In Supervised Spectral Classifiers For On-Board Hyperspectral Imaging: An Overview
Rotation Equivariant Convolutional Neural Networks For Hyperspectral Image Classification
Inference In Supervised Spectral Classifiers For On-Board Hyperspectral Imaging: An Overview
Rotation Equivariant Convolutional Neural Networks For Hyperspectral Image Classification
U-Img2dsm: Unpaired Simulation Of Digital Surface Models With Generative Adversarial Networks
Rotation Equivariant Convolutional Neural Networks For Hyperspectral Image Classification
U-Img2dsm: Unpaired Simulation Of Digital Surface Models With Generative Adversarial Networks
Flop-Reduction Through Memory Allocations Within Cnn For Hyperspectral Image Classification
U-Img2dsm: Unpaired Simulation Of Digital Surface Models With Generative Adversarial Networks
Flop-Reduction Through Memory Allocations Within Cnn For Hyperspectral Image Classification
Efficient Convolutional Neural Network For Spectral-Spatial Hyperspectral Denoising
Flop-Reduction Through Memory Allocations Within Cnn For Hyperspectral Image Classification
Efficient Convolutional Neural Network For Spectral-Spatial Hyperspectral Denoising
Gpu Parallel Implementation Of Dual-Depth Sparse Probabilistic Latent Semantic Analysis For Hyperspectral Unmixing
Efficient Convolutional Neural Network For Spectral-Spatial Hyperspectral Denoising
Gpu Parallel Implementation Of Dual-Depth Sparse Probabilistic Latent Semantic Analysis For Hyperspectral Unmixing
Solving Deep Neural Networks With Ordinary Differential Equations For Remotely Sensed Hyperspectral Image Classification
Gpu Parallel Implementation Of Dual-Depth Sparse Probabilistic Latent Semantic Analysis For Hyperspectral Unmixing
Solving Deep Neural Networks With Ordinary Differential Equations For Remotely Sensed Hyperspectral Image Classification
Open Multi-Processing Acceleration For Unsupervised Land Cover Categorization Using Probabilistic Latent Semantic Analysis
Solving Deep Neural Networks With Ordinary Differential Equations For Remotely Sensed Hyperspectral Image Classification
Open Multi-Processing Acceleration For Unsupervised Land Cover Categorization Using Probabilistic Latent Semantic Analysis
Accessibility-Free Active Learning For Hyperspectral Image Classification
Open Multi-Processing Acceleration For Unsupervised Land Cover Categorization Using Probabilistic Latent Semantic Analysis
Accessibility-Free Active Learning For Hyperspectral Image Classification
Low-High-Power Consumption Architectures For Deep-Learning Models Applied To Hyperspectral Image Classification
Accessibility-Free Active Learning For Hyperspectral Image Classification
Low-High-Power Consumption Architectures For Deep-Learning Models Applied To Hyperspectral Image Classification
Capsule Networks For Hyperspectral Image Classification
Low-High-Power Consumption Architectures For Deep-Learning Models Applied To Hyperspectral Image Classification
Capsule Networks For Hyperspectral Image Classification
Deep Pyramidal Residual Networks For Spectral-Spatial Hyperspectral Image Classification
Capsule Networks For Hyperspectral Image Classification
Deep Pyramidal Residual Networks For Spectral-Spatial Hyperspectral Image Classification
Feature Extraction With Multiscale Covariance Maps For Hyperspectral Image Classification
Deep Pyramidal Residual Networks For Spectral-Spatial Hyperspectral Image Classification
Feature Extraction With Multiscale Covariance Maps For Hyperspectral Image Classification
A Comparative Study Of Techniques For Hyperspectral Image Classification
Feature Extraction With Multiscale Covariance Maps For Hyperspectral Image Classification
A Comparative Study Of Techniques For Hyperspectral Image Classification
Cloud Deep Networks For Hyperspectral Image Analysis
A Comparative Study Of Techniques For Hyperspectral Image Classification
Cloud Deep Networks For Hyperspectral Image Analysis
Deep Learning Classifiers For Hyperspectral Imaging: A Review
Cloud Deep Networks For Hyperspectral Image Analysis
Deep Learning Classifiers For Hyperspectral Imaging: A Review
Hyperspectral Image Classification Using Random Occlusion Data Augmentation
Deep Learning Classifiers For Hyperspectral Imaging: A Review
Hyperspectral Image Classification Using Random Occlusion Data Augmentation
Remote Sensing Image Superresolution Using Deep Residual Channel Attention
Hyperspectral Image Classification Using Random Occlusion Data Augmentation
Remote Sensing Image Superresolution Using Deep Residual Channel Attention
Visual Attention-Driven Hyperspectral Image Classification
Remote Sensing Image Superresolution Using Deep Residual Channel Attention
Visual Attention-Driven Hyperspectral Image Classification
Remote Sensing Single-Image Superresolution Based On A Deep Compendium Model
Visual Attention-Driven Hyperspectral Image Classification
Remote Sensing Single-Image Superresolution Based On A Deep Compendium Model
A New Deep Generative Network For Unsupervised Remote Sensing Single-Image Super-Resolution
Remote Sensing Single-Image Superresolution Based On A Deep Compendium Model
A New Deep Generative Network For Unsupervised Remote Sensing Single-Image Super-Resolution
Active Learning With Convolutional Neural Networks For Hyperspectral Image Classification Using A New Bayesian Approach
A New Deep Generative Network For Unsupervised Remote Sensing Single-Image Super-Resolution
Active Learning With Convolutional Neural Networks For Hyperspectral Image Classification Using A New Bayesian Approach
A New Deep Convolutional Neural Network For Fast Hyperspectral Image Classification
Active Learning With Convolutional Neural Networks For Hyperspectral Image Classification Using A New Bayesian Approach
A New Deep Convolutional Neural Network For Fast Hyperspectral Image Classification
Evaluation Of Different Regularization Methods For The Extreme Learning Machine Applied To Hyperspectral Images
A New Deep Convolutional Neural Network For Fast Hyperspectral Image Classification
Evaluation Of Different Regularization Methods For The Extreme Learning Machine Applied To Hyperspectral Images
An Investigation On Self-Normalized Deep Neural Networks For Hyperspectral Image Classification
Evaluation Of Different Regularization Methods For The Extreme Learning Machine Applied To Hyperspectral Images
An Investigation On Self-Normalized Deep Neural Networks For Hyperspectral Image Classification
Inter-Sensor Regression Analysis For Operational Sentinel-2 And Sentinel-3 Data Products
An Investigation On Self-Normalized Deep Neural Networks For Hyperspectral Image Classification
Inter-Sensor Regression Analysis For Operational Sentinel-2 And Sentinel-3 Data Products
Fast Dimensionality Reduction And Classification Of Hyperspectral Images With Extreme Learning Machines
Inter-Sensor Regression Analysis For Operational Sentinel-2 And Sentinel-3 Data Products
Fast Dimensionality Reduction And Classification Of Hyperspectral Images With Extreme Learning Machines
Deep & Dense Convolutional Neural Network For Hyperspectral Image Classification
Fast Dimensionality Reduction And Classification Of Hyperspectral Images With Extreme Learning Machines
Deep & Dense Convolutional Neural Network For Hyperspectral Image Classification
Multimodal Probabilistic Latent Semantic Analysis For Sentinel-1 And Sentinel-2 Image Fusion
Deep & Dense Convolutional Neural Network For Hyperspectral Image Classification
Multimodal Probabilistic Latent Semantic Analysis For Sentinel-1 And Sentinel-2 Image Fusion
Remote Sensing Image Fusion Using Hierarchical Multimodal Probabilistic Latent Semantic Analysis
Multimodal Probabilistic Latent Semantic Analysis For Sentinel-1 And Sentinel-2 Image Fusion
Remote Sensing Image Fusion Using Hierarchical Multimodal Probabilistic Latent Semantic Analysis
Multicore Implementation Of The Multi-Scale Adaptive Deep Pyramid Matching Model For Remotely Sensed Image Classification
Remote Sensing Image Fusion Using Hierarchical Multimodal Probabilistic Latent Semantic Analysis
Multicore Implementation Of The Multi-Scale Adaptive Deep Pyramid Matching Model For Remotely Sensed Image Classification
Onboard Payload-Data Dimensionality Reduction
Multicore Implementation Of The Multi-Scale Adaptive Deep Pyramid Matching Model For Remotely Sensed Image Classification
Onboard Payload-Data Dimensionality Reduction
Cloud Implementation Of The K-Means Algorithm For Hyperspectral Image Analysis
Onboard Payload-Data Dimensionality Reduction
Cloud Implementation Of The K-Means Algorithm For Hyperspectral Image Analysis
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Cloud Implementation Of The K-Means Algorithm For Hyperspectral Image Analysis
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Transformer-Based Network For Enhanced Wireless Service Differentiation In 6g
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