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portfolio
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publications
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Your Name, You. (2009). "Paper Title Number 1." Journal 1. 1(1).
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Your Name, You. (2010). "Paper Title Number 2." Journal 1. 1(2).
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A navigation agent for mobile manipulators
M. Haut, L. Manso, D. Gallego, M. Paoletti, P. Bustos, A. Bandera, A. Romero-Garcés, "A navigation agent for mobile manipulators." Advances in Intelligent Systems and Computing, 2016.
cited By 6
Cloud implementation of the K-means algorithm for hyperspectral image analysis
J.M. Haut, M. Paoletti, J. Plaza, A. Plaza, "Cloud implementation of the K-means algorithm for hyperspectral image analysis." Journal of Supercomputing, 2017.
cited By 88
Multicore implementation of the multi-scale adaptive deep pyramid matching model for remotely sensed image classification
M.E. Paoletti, J.M. Haut, J. Plaza, A. Plaza, Q. Liu, R. Hang, "Multicore implementation of the multi-scale adaptive deep pyramid matching model for remotely sensed image classification." International Geoscience and Remote Sensing Symposium (IGARSS), 2017.
cited By 4
Onboard payload-data dimensionality reduction
M. Penalver, F. Del, M.E. Paoletti, J.M. Haut, J. Plaza, A. Plaza, "Onboard payload-data dimensionality reduction." International Geoscience and Remote Sensing Symposium (IGARSS), 2017.
cited By 3
A new deep convolutional neural network for fast hyperspectral image classification
M.E. Paoletti, J.M. Haut, J. Plaza, A. Plaza, "A new deep convolutional neural network for fast hyperspectral image classification." ISPRS Journal of Photogrammetry and Remote Sensing, 2018.
cited By 364
A new deep generative network for unsupervised remote sensing single-image super-resolution
J.M. Haut, R. Fernandez-Beltran, M.E. Paoletti, J. Plaza, A. Plaza, F. Pla, "A new deep generative network for unsupervised remote sensing single-image super-resolution." IEEE Transactions on Geoscience and Remote Sensing, 2018.
cited By 117
Active learning with convolutional neural networks for hyperspectral image classification using a new bayesian approach
J.M. Haut, M.E. Paoletti, J. Plaza, J. Li, A. Plaza, "Active learning with convolutional neural networks for hyperspectral image classification using a new bayesian approach." IEEE Transactions on Geoscience and Remote Sensing, 2018.
cited By 181
An investigation on self-normalized deep neural networks for hyperspectral image classification
M.E. Paoletti, J.M. Haut, J. Plaza, A. Plaza, "An investigation on self-normalized deep neural networks for hyperspectral image classification." International Geoscience and Remote Sensing Symposium (IGARSS), 2018.
cited By 4
Deep & Dense convolutional neural network for hyperspectral image classification
M.E. Paoletti, J.M. Haut, J. Plaza, A. Plaza, "Deep & Dense convolutional neural network for hyperspectral image classification." Remote Sensing, 2018.
cited By 72
Evaluation of different regularization methods for the extreme learning machine applied to hyperspectral images
J.M. Haut, Y. Liu, M.E. Paoletti, X. Xu, J. Plaza, A. Plaza, "Evaluation of different regularization methods for the extreme learning machine applied to hyperspectral images." International Geoscience and Remote Sensing Symposium (IGARSS), 2018.
cited By 1
Fast dimensionality reduction and classification of hyperspectral images with extreme learning machines
J.M. Haut, M.E. Paoletti, J. Plaza, A. Plaza, "Fast dimensionality reduction and classification of hyperspectral images with extreme learning machines." Journal of Real-Time Image Processing, 2018.
cited By 33
Inter-sensor regression analysis for operational sentinel-2 and sentinel-3 data products
J.M. Haut, R. Fernandez-Beltran, M.E. Paoletti, J. Plaza, A. Plaza, F. Pla, "Inter-sensor regression analysis for operational sentinel-2 and sentinel-3 data products." International Geoscience and Remote Sensing Symposium (IGARSS), 2018.
cited By 0
Multimodal probabilistic latent semantic analysis for Sentinel-1 and Sentinel-2 image fusion
R. Fernandez-Beltran, J.M. Haut, M.E. Paoletti, J. Plaza, A. Plaza, F. Pla, "Multimodal probabilistic latent semantic analysis for Sentinel-1 and Sentinel-2 image fusion." IEEE Geoscience and Remote Sensing Letters, 2018.
cited By 28
Remote Sensing Image Fusion Using Hierarchical Multimodal Probabilistic Latent Semantic Analysis
R. Fernandez-Beltran, J.M. Haut, M.E. Paoletti, J. Plaza, A. Plaza, F. Pla, "Remote Sensing Image Fusion Using Hierarchical Multimodal Probabilistic Latent Semantic Analysis." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2018.
cited By 51
A comparative study of techniques for hyperspectral image classification [Estudio comparativo de técnicas de clasificación de imágenes hiperespectrales]
M.E. Paolettia, J.M. Haut, J. Plaza, A. Plaza, "A comparative study of techniques for hyperspectral image classification [Estudio comparativo de técnicas de clasificación de imágenes hiperespectrales]." RIAI - Revista Iberoamericana de Automatica e Informatica Industrial, 2019.
cited By 11
Accessibility-Free Active Learning for Hyperspectral Image Classification
C. Liu, J. Li, M.E. Paoletti, J.M. Haut, A. Plaza, Q. Shi, "Accessibility-Free Active Learning for Hyperspectral Image Classification." International Geoscience and Remote Sensing Symposium (IGARSS), 2019.
cited By 1
Capsule Networks for Hyperspectral Image Classification
M.E. Paoletti, J.M. Haut, R. Fernandez-Beltran, J. Plaza, A. Plaza, J. Li, F. Pla, "Capsule Networks for Hyperspectral Image Classification." IEEE Transactions on Geoscience and Remote Sensing, 2019.
cited By 231
Cloud deep networks for hyperspectral image analysis
J.M. Haut, J.A. Gallardo, M.E. Paoletti, G. Cavallaro, J. Plaza, A. Plaza, M. Riedel, "Cloud deep networks for hyperspectral image analysis." IEEE Transactions on Geoscience and Remote Sensing, 2019.
cited By 18
Deep learning classifiers for hyperspectral imaging: A review
M.E. Paoletti, J.M. Haut, J. Plaza, A. Plaza, "Deep learning classifiers for hyperspectral imaging: A review." ISPRS Journal of Photogrammetry and Remote Sensing, 2019.
cited By 419
Deep pyramidal residual networks for spectral-spatial hyperspectral image classification
M.E. Paoletti, J.M. Haut, R. Fernandez-Beltran, J. Plaza, A.J. Plaza, F. Pla, "Deep pyramidal residual networks for spectral-spatial hyperspectral image classification." IEEE Transactions on Geoscience and Remote Sensing, 2019.
cited By 263
Efficient Convolutional Neural Network for Spectral-Spatial Hyperspectral Denoising
A. Maffei, J.M. Haut, M.E. Paoletti, J. Plaza, L. Bruzone, A. Plaza, "Efficient Convolutional Neural Network for Spectral-Spatial Hyperspectral Denoising." Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing, 2019.
cited By 0
Feature extraction with multiscale covariance maps for hyperspectral image classification
N. He, M.E. Paoletti, J.M. Haut, L. Fang, S. Li, A. Plaza, J. Plaza, "Feature extraction with multiscale covariance maps for hyperspectral image classification." IEEE Transactions on Geoscience and Remote Sensing, 2019.
cited By 148
GPU Parallel Implementation of Dual-Depth Sparse Probabilistic Latent Semantic Analysis for Hyperspectral Unmixing
J.A.G. Jaramago, M.E. Paoletti, J.M. Haut, R. Fernandez-Beltran, A. Plaza, J. Plaza, "GPU Parallel Implementation of Dual-Depth Sparse Probabilistic Latent Semantic Analysis for Hyperspectral Unmixing." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2019.
cited By 8
Hyperspectral Image Classification Using Random Occlusion Data Augmentation
J.M. Haut, M.E. Paoletti, J. Plaza, A. Plaza, J. Li, "Hyperspectral Image Classification Using Random Occlusion Data Augmentation." IEEE Geoscience and Remote Sensing Letters, 2019.
cited By 60
Low-High-Power Consumption Architectures for Deep-Learning Models Applied to Hyperspectral Image Classification
J.M. Haut, S. Bernabé, M.E. Paoletti, R. Fernandez-Beltran, A. Plaza, J. Plaza, "Low-High-Power Consumption Architectures for Deep-Learning Models Applied to Hyperspectral Image Classification." IEEE Geoscience and Remote Sensing Letters, 2019.
cited By 25
Open Multi-Processing Acceleration for Unsupervised Land Cover Categorization Using Probabilistic Latent Semantic Analysis
S. Bernabe, C. Garcia, R. Fernandez-Beltran, M.E. Paoletti, J.M. Haut, J. Plaza, A. Plaza, "Open Multi-Processing Acceleration for Unsupervised Land Cover Categorization Using Probabilistic Latent Semantic Analysis." International Geoscience and Remote Sensing Symposium (IGARSS), 2019.
cited By 0
Remote Sensing Image Superresolution Using Deep Residual Channel Attention
J.M. Haut, R. Fernandez-Beltran, M.E. Paoletti, J. Plaza, A. Plaza, "Remote Sensing Image Superresolution Using Deep Residual Channel Attention." IEEE Transactions on Geoscience and Remote Sensing, 2019.
cited By 54
Remote sensing single-image superresolution based on a deep compendium model
J.M. Haut, M.E. Paoletti, R. Fernandez-Beltran, J. Plaza, A. Plaza, J. Li, "Remote sensing single-image superresolution based on a deep compendium model." IEEE Geoscience and Remote Sensing Letters, 2019.
cited By 21
Solving Deep Neural Networks with Ordinary Differential Equations for Remotely Sensed Hyperspectral Image Classification
M.E. Paoletti, J.M. Haut, J. Plaza, A. Plaza, "Solving Deep Neural Networks with Ordinary Differential Equations for Remotely Sensed Hyperspectral Image Classification." International Geoscience and Remote Sensing Symposium (IGARSS), 2019.
cited By 0
Visual Attention-Driven Hyperspectral Image Classification
J.M. Haut, M.E. Paoletti, J. Plaza, A. Plaza, J. Li, "Visual Attention-Driven Hyperspectral Image Classification." IEEE Transactions on Geoscience and Remote Sensing, 2019.
cited By 136
A Single Model CNN for Hyperspectral Image Denoising
A. Maffei, J.M. Haut, M.E. Paoletti, J. Plaza, L. Bruzzone, A. Plaza, "A Single Model CNN for Hyperspectral Image Denoising." IEEE Transactions on Geoscience and Remote Sensing, 2020.
cited By 65
A new GPU implementation of support vector machines for fast hyperspectral image classification
M.E. Paoletti, J.M. Haut, X. Tao, J.P. Miguel, A. Plaza, "A new GPU implementation of support vector machines for fast hyperspectral image classification." Remote Sensing, 2020.
cited By 23
Inference in supervised spectral classifiers for on-board hyperspectral imaging: An overview
A. Alcolea, M.E. Paoletti, J.M. Haut, J. Resano, A. Plaza, "Inference in supervised spectral classifiers for on-board hyperspectral imaging: An overview." Remote Sensing, 2020.
cited By 24
Neighboring Region Dropout for Hyperspectral Image Classification
M.E. Paoletti, J.M. Haut, J. Plaza, A. Plaza, "Neighboring Region Dropout for Hyperspectral Image Classification." IEEE Geoscience and Remote Sensing Letters, 2020.
cited By 8
Neural Ordinary Differential Equations for Hyperspectral Image Classification
M.E. Paoletti, J.M. Haut, J. Plaza, A. Plaza, "Neural Ordinary Differential Equations for Hyperspectral Image Classification." IEEE Transactions on Geoscience and Remote Sensing, 2020.
cited By 11
Rotation equivariant convolutional neural networks for hyperspectral image classification
M.E. Paoletti, J.M. Haut, S.K. Roy, E.M.T. Hendrix, "Rotation equivariant convolutional neural networks for hyperspectral image classification." IEEE Access, 2020.
cited By 15
Scalable recurrent neural network for hyperspectral image classification
M.E. Paoletti, J.M. Haut, J. Plaza, A. Plaza, "Scalable recurrent neural network for hyperspectral image classification." Journal of Supercomputing, 2020.
cited By 29
Training Capsnets via Active Learning for Hyperspectral Image Classification
M.E. Paoletti, J.M. Haut, J. Plaza, A. Plaza, "Training Capsnets via Active Learning for Hyperspectral Image Classification." International Geoscience and Remote Sensing Symposium (IGARSS), 2020.
cited By 4
Training deep neural networks: a static load balancing approach
S. Moreno-Álvarez, J.M. Haut, M.E. Paoletti, J.A. Rico-Gallego, J.C. Díaz-Martín, J. Plaza, "Training deep neural networks: a static load balancing approach." Journal of Supercomputing, 2020.
cited By 8
A New Max-Min Convolutional Network for Hyperspectral Image Classification
S.K. Roy, M.E. Paoletti, J.M. Haut, E.M.T. Hendrix, A. Plaza, "A New Max-Min Convolutional Network for Hyperspectral Image Classification." Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing, 2021.
cited By 3
A recommendation system for electronic health records in the context of the HOPE project
R.V. Gonzalez, A. Robles-Gomez, R. Pastor-Vargas, J.M. Haut, N.A. Passadore, M.E. Paoletti, C.L. Sanchez, L. Tobarra, K.A. Chacon-Vargas, R.H. Berlinches, F.S. Rubio, "A recommendation system for electronic health records in the context of the HOPE project." Proceedings - IEEE Symposium on Computer-Based Medical Systems, 2021.
cited By 0
ADAPTING KERNELS FOR HYPERSPECTRAL IMAGE CLASSIFICATION
J.M. Haut, M.E. Paoletti, R. Pastor-Vargas, Ll. Tobarra, A. Robles-Gomez, R. Hernandez, E.M.T. Hendrix, J. Li, "ADAPTING KERNELS FOR HYPERSPECTRAL IMAGE CLASSIFICATION." International Geoscience and Remote Sensing Symposium (IGARSS), 2021.
cited By 0
Adaptable convolutional network for hyperspectral image classification
M.E. Paoletti, J.M. Haut, "Adaptable convolutional network for hyperspectral image classification." Remote Sensing, 2021.
cited By 5
Analysis of Remotely Sensed Images through Social Media
A. Redondo, J.M. Haut, M.E. Paoletti, X. Tao, J. Plaza, A. Plaza, "Analysis of Remotely Sensed Images through Social Media." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021.
cited By 1
Analyzing the users’ acceptance of an IoT cloud platform using the UTAUT/TAM model
L. Tobarra, J.M. Haut, R. Hernández, R. Pastor-Vargas, A. Robles-Gómez, "Analyzing the users’ acceptance of an IoT cloud platform using the UTAUT/TAM model." IEEE Access, 2021.
cited By 3
Deep mixed precision for hyperspectral image classification
M.E. Paoletti, X. Tao, J.M. Haut, S. Moreno-Álvarez, A. Plaza, "Deep mixed precision for hyperspectral image classification." Journal of Supercomputing, 2021.
cited By 4
Distributed Deep Learning for Remote Sensing Data Interpretation
J.M. Haut, M.E. Paoletti, S. Moreno-Alvarez, J. Plaza, J.-A. Rico-Gallego, A. Plaza, "Distributed Deep Learning for Remote Sensing Data Interpretation." Proceedings of the IEEE, 2021.
cited By 6
Endmember estimation with maximum distance analysis
X. Tao, M.E. Paoletti, J.M. Haut, P. Ren, J. Plaza, A. Plaza, "Endmember estimation with maximum distance analysis." Remote Sensing, 2021.
cited By 7
FLOP-Reduction through Memory Allocations within CNN for Hyperspectral Image Classification
M.E. Paoletti, J.M. Haut, X. Tao, J. Plaza, A. Plaza, "FLOP-Reduction through Memory Allocations within CNN for Hyperspectral Image Classification." IEEE Transactions on Geoscience and Remote Sensing, 2021.
cited By 24
Ghostnet for Hyperspectral Image Classification
M.E. Paoletti, J.M. Haut, N.S. Pereira, J. Plaza, A. Plaza, "Ghostnet for Hyperspectral Image Classification." IEEE Transactions on Geoscience and Remote Sensing, 2021.
cited By 42
Heterogeneous model parallelism for deep neural networks
S. Moreno-Alvarez, J.M. Haut, M.E. Paoletti, J.A. Rico-Gallego, "Heterogeneous model parallelism for deep neural networks." Neurocomputing, 2021.
cited By 5
MULTIPLE INCREMENTAL KERNEL CONVOLUTION FOR LAND COVER CLASSIFICATION OF REMOTELY SENSED IMAGES
X. Tao, L. Han, M.E. Paoletti, S.K. Roy, J. Plaza, J.M. Haut, A. Plaza, "MULTIPLE INCREMENTAL KERNEL CONVOLUTION FOR LAND COVER CLASSIFICATION OF REMOTELY SENSED IMAGES." International Geoscience and Remote Sensing Symposium (IGARSS), 2021.
cited By 1
Morphological Convolutional Neural Networks for Hyperspectral Image Classification
S. Roy, R. Mondal, M.E. Paoletti, J.M. Haut, A. Plaza, "Morphological Convolutional Neural Networks for Hyperspectral Image Classification." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021.
cited By 26
Multibranch Selective Kernel Networks for Hyperspectral Image Classification
T. Alipour-Fard, M.E. Paoletti, J.M. Haut, H. Arefi, J. Plaza, A. Plaza, "Multibranch Selective Kernel Networks for Hyperspectral Image Classification." IEEE Geoscience and Remote Sensing Letters, 2021.
cited By 19
On the Evaluation of Machine Learning Algorithms for Hyperspectral Image Classification on a Heterogeneous Computing Device
N. Pereira, J. Plaza, J.M. Haut, A. Plaza, "On the Evaluation of Machine Learning Algorithms for Hyperspectral Image Classification on a Heterogeneous Computing Device." Iberian Conference on Information Systems and Technologies, CISTI, 2021.
cited By 0
SiCoDeF² Net: Siamese Convolution Deconvolution Feature Fusion Network for One-Shot Classification
S.K. Roy, P. Kar, M.E. Paoletti, J.M. Haut, R. Pastor-Vargas, A. Robles-Gomez, "SiCoDeF² Net: Siamese Convolution Deconvolution Feature Fusion Network for One-Shot Classification." IEEE Access, 2021.
cited By 2
Studying the students' learning in LoT@UNED
L. Tobarra, A. Robles-Gomez, R. Pastor-Vargas, R. Hernandez, J.M. Haut, "Studying the students' learning in LoT@UNED." IEEE Global Engineering Education Conference, EDUCON, 2021.
cited By 1
U-IMG2DSM: Unpaired Simulation of Digital Surface Models with Generative Adversarial Networks
M.E. Paoletti, J.M. Haut, P. Ghamisi, N. Yokoya, J. Plaza, A. Plaza, "U-IMG2DSM: Unpaired Simulation of Digital Surface Models with Generative Adversarial Networks." IEEE Geoscience and Remote Sensing Letters, 2021.
cited By 12
A New 3D Convolution Network for Hyperspectral Unmixing
X. Tao, M.E. Paoletti, L. Han, Z. Wu, L.I. Jimenez, J.M. Haut, P. Ren, J. Plaza, A. Plaza, "A New 3D Convolution Network for Hyperspectral Unmixing." International Geoscience and Remote Sensing Symposium (IGARSS), 2022.
cited By 0
A New Deep Convolutional Network for Effective Hyperspectral Unmixing
X. Tao, M.E. Paoletti, L. Han, Z. Wu, P. Ren, J. Plaza, A. Plaza, J.M. Haut, "A New Deep Convolutional Network for Effective Hyperspectral Unmixing." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022.
cited By 2
Adaptive Dictionary Construction for Hyperspectral Anomaly Detection Based on Collaborative Representation
Z. Wu, H. Su, X. Tao, L. Han, M.E. Paoletti, J.M. Haut, J. Plaza, A. Plaza, "Adaptive Dictionary Construction for Hyperspectral Anomaly Detection Based on Collaborative Representation." International Geoscience and Remote Sensing Symposium (IGARSS), 2022.
cited By 0
Bi-Dimensional Vector Data Analysis of Positional Accuracy of Landsat-8 Image with Pycircularstats
A. Cuartero, M.E. Paoletti, A.R. Presas, J.M. Haut, "Bi-Dimensional Vector Data Analysis of Positional Accuracy of Landsat-8 Image with Pycircularstats." International Geoscience and Remote Sensing Symposium (IGARSS), 2022.
cited By 0
Deep Attention-Driven HSI Scene Classification Based on Inverted Dot-Product
M.E. Paoletti, X. Tao, L. Han, Z. Wu, S. Moreno-Alvarez, J.M. Haut, "Deep Attention-Driven HSI Scene Classification Based on Inverted Dot-Product." International Geoscience and Remote Sensing Symposium (IGARSS), 2022.
cited By 0
Efficient Semantic Segmentation of Hyperspectral Images Using Adaptable Rectangular Convolution
J.L. Garcia, M.E. Paoletti, L.I. Jimenez, J.M. Haut, A. Plaza, "Efficient Semantic Segmentation of Hyperspectral Images Using Adaptable Rectangular Convolution." IEEE Geoscience and Remote Sensing Letters, 2022.
cited By 1
Endmember Estimation from Hyperspectral Images Using Geometric Distances
X. Tao, M.E. Paoletti, J.M. Haut, L. Han, P. Ren, J. Plaza, A. Plaza, "Endmember Estimation from Hyperspectral Images Using Geometric Distances." IEEE Geoscience and Remote Sensing Letters, 2022.
cited By 3
Fast Orthogonal Projection for Hyperspectral Unmixing
X. Tao, M.E. Paoletti, L. Han, J.M. Haut, P. Ren, J. Plaza, A. Plaza, "Fast Orthogonal Projection for Hyperspectral Unmixing." IEEE Transactions on Geoscience and Remote Sensing, 2022.
cited By 1
GPU-Friendly Neural Networks for Remote Sensing Scene Classification
J.M. Haut, A. Alcolea, M.E. Paoletti, J. Plaza, J. Resano, A. Plaza, "GPU-Friendly Neural Networks for Remote Sensing Scene Classification." IEEE Geoscience and Remote Sensing Letters, 2022.
cited By 6
Generative Adversarial Minority Oversampling for Spectral-Spatial Hyperspectral Image Classification
S.K. Roy, J.M. Haut, M.E. Paoletti, S.R. Dubey, A. Plaza, "Generative Adversarial Minority Oversampling for Spectral-Spatial Hyperspectral Image Classification." IEEE Transactions on Geoscience and Remote Sensing, 2022.
cited By 35
Heterogeneous gradient computing optimization for scalable deep neural networks
S. Moreno-Álvarez, M.E. Paoletti, J.A. Rico-Gallego, J.M. Haut, "Heterogeneous gradient computing optimization for scalable deep neural networks." Journal of Supercomputing, 2022.
cited By 1
Hyperspectral Anomaly Detection With Relaxed Collaborative Representation
Z. Wu, H. Su, X. Tao, L. Han, M.E. Paoletti, J.M. Haut, J. Plaza, A. Plaza, "Hyperspectral Anomaly Detection With Relaxed Collaborative Representation." IEEE Transactions on Geoscience and Remote Sensing, 2022.
cited By 3
Multiple Attention-Guided Capsule Networks for Hyperspectral Image Classification
M.E. Paoletti, S. Moreno-Alvarez, J.M. Haut, "Multiple Attention-Guided Capsule Networks for Hyperspectral Image Classification." IEEE Transactions on Geoscience and Remote Sensing, 2022.
cited By 11
On Training Set Selection in Spatial Deep Learning
E.M.T. Hendrix, M. Paoletti, J.M. Haut, "On Training Set Selection in Spatial Deep Learning." Springer Optimization and Its Applications, 2022.
cited By 1
Optimizing Distributed Deep Learning in Heterogeneous Computing Platforms for Remote Sensing Data Classification
S. Moreno-Alvarez, M.E. Paoletti, J.A. Rico, G. Cavallaro, J.M. Haut, "Optimizing Distributed Deep Learning in Heterogeneous Computing Platforms for Remote Sensing Data Classification." International Geoscience and Remote Sensing Symposium (IGARSS), 2022.
cited By 0
PyCircularStats: A Python-Based Tool for Remote Sensing Circular Statistics and Graphical Analysis
A. Cuartero, M.E. Paoletti, P. Garcia-Rodriguez, J.M. Haut, "PyCircularStats: A Python-Based Tool for Remote Sensing Circular Statistics and Graphical Analysis." International Geoscience and Remote Sensing Symposium (IGARSS), 2022.
cited By 0
Remote Sensing Image Classification Using CNNs With Balanced Gradient for Distributed Heterogeneous Computing
S. Moreno-Alvarez, M.E. Paoletti, G. Cavallaro, J.A. Rico, J.M. Haut, "Remote Sensing Image Classification Using CNNs With Balanced Gradient for Distributed Heterogeneous Computing." IEEE Geoscience and Remote Sensing Letters, 2022.
cited By 0
Separable Attention Network in Single- And Mixed-Precision Floating Point for Land-Cover Classification of Remote Sensing Images
M.E. Paoletti, J.M. Haut, T. Alipour-Fard, S.K. Roy, E.M.T. Hendrix, A. Plaza, "Separable Attention Network in Single- And Mixed-Precision Floating Point for Land-Cover Classification of Remote Sensing Images." IEEE Geoscience and Remote Sensing Letters, 2022.
cited By 2
Central Cohesion Gradual Hashing for Remote Sensing Image Retrieval
L. Han, M.E. Paoletti, X. Tao, Z. Wu, J.M. Haut, J. Plaza, A. Plaza, "Central Cohesion Gradual Hashing for Remote Sensing Image Retrieval." IEEE Geoscience and Remote Sensing Letters, 2023.
cited By 0
Spectral-Spatial Morphological Attention Transformer for Hyperspectral Image Classification
S.K. Roy, A. Deria, C. Shah, J.M. Haut, Q. Du, A. Plaza, "Spectral-Spatial Morphological Attention Transformer for Hyperspectral Image Classification." IEEE Transactions on Geoscience and Remote Sensing, 2023.