PUBLICACIÓN

FLOP-Reduction Through Memory Allocations Within CNN for Hyperspectral Image Classification

ACCEDER A LA PUBLICACIÓN: Orcid

2020 IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING

Earth and Planetary Sciences (miscellaneous) (Q1), Electrical and Electronic Engineering (Q1)

JCR: 5.6

SJR: 2.141

DOI

10.1109/tgrs.2020.3024730

ISSN

0196-2892

AUTORES DE LA UEX

Mercedes Eugenia Paoletti Ávila

OTRAS PUBLICACIONES DE INTERÉS

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Typical Mineral Abundance Estimation Of Chang'e-3 Yutu Rover With Hyperspectral Data Based On Diffusion Autoencoder Unmixing Model
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Typical Mineral Abundance Estimation Of Chang'e-3 Yutu Rover With Hyperspectral Data Based On Diffusion Autoencoder Unmixing Model
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Hash-Based Remote Sensing Image Retrieval
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Hash-Based Remote Sensing Image Retrieval
Hyperspectral Image Analysis Using Cloud-Based Support Vector Machines
Hash-Based Remote Sensing Image Retrieval
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An Abundance-Guided Attention Network For Hyperspectral Unmixing
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Decentralized Mechanism For Edge Node Allocation In Access Network: An Experimental Evaluation
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Deep Mixed Precision For Hyperspectral Image Classification
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Flop-Reduction Through Memory Allocations Within Cnn For Hyperspectral Image Classification
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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
Morphological Convolutional Neural Networks For Hyperspectral Image Classification
Sicodef² Net: Siamese Convolution Deconvolution Feature Fusion Network For One-Shot Classification
Morphological Convolutional Neural Networks For Hyperspectral Image 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
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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
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A Single Model Cnn For Hyperspectral Image Denoising
A New Gpu Implementation Of Support Vector Machines For Fast Hyperspectral Image Classification
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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
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Flop-Reduction Through Memory Allocations Within Cnn For Hyperspectral Image Classification
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Flop-Reduction Through Memory Allocations Within Cnn For Hyperspectral Image Classification
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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
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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
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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
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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
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Active Learning With Convolutional Neural Networks For Hyperspectral Image Classification Using A New Bayesian Approach
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Inter-Sensor Regression Analysis For Operational Sentinel-2 And Sentinel-3 Data Products
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Inter-Sensor Regression Analysis For Operational Sentinel-2 And Sentinel-3 Data Products
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Deep & Dense Convolutional Neural Network For Hyperspectral Image Classification
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Multimodal Probabilistic Latent Semantic Analysis For Sentinel-1 And Sentinel-2 Image Fusion
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