Listar por autoría "f0425174-76b6-4ce5-accf-5e4f2bba8109"
Mostrando ítems 1-20 de 31
-
A New Deep Generative Network for Unsupervised Remote Sensing Single-Image Super-Resolution
Haut, Juan M.; Fernandez-Beltran, Ruben; Paoletti, Mercedes Eugenia; Plaza, Javier; Plaza, Antonio; Pla, Filiberto IEEE (2018-11)Super-resolution (SR) brings an excellent opportunity to improve a wide range of different remote sensing applications. SR techniques are concerned about increasing the image resolution while providing finer spatial details ... -
Assessing the Performance-Energy Balance of Graphics Processors for Spectral Unmixing
Sánchez, S.; León Navarro, Germán; Plaza, Antonio; Quintana-Orti, Enrique S. IEEE (2014)Remotely sensed hyperspectral imaging missions are often limited by onboard power restrictions while, simultaneously, require high computing power in order to address applications with relevant constraints in terms of ... -
Capsule Networks for Hyperspectral Image Classification
Paoletti, Mercedes Eugenia; Haut, Juan M.; Fernandez-Beltran, Ruben; Plaza, Javier; Plaza, Antonio; Li, Jun; Pla, Filiberto IEEE (2018-10)Convolutional neural networks (CNNs) have recently exhibited an excellent performance in hyperspectral image classification tasks. However, the straightforward CNN-based network architecture still finds obstacles when ... -
Deep Learning-Based Building Footprint Extraction With Missing Annotations
kang, jian; Fernandez-Beltran, Ruben; Sun, Xian; Ni, Jingen; Plaza, Antonio Institute of Electrical and Electronics Engineers (2021-04-21)Most state-of-the-art deep learning-based methods for extraction of building footprints are aimed at designing proper convolutional neural network (CNN) architectures or loss functions able to effectively predict building ... -
Deep Metric Learning Based on Scalable Neighborhood Components for Remote Sensing Scene Characterization
kang, jian; Fernandez-Beltran, Ruben; Zhen, Ye; Tong, Xiaohua; Ghamisi, Pedram; Plaza, Antonio Institute of Electrical and Electronics Engineers (2020-05-12)With the development of convolutional neural networks (CNNs), the semantic understanding of remote sensing (RS) scenes has been significantly improved based on their prominent feature encoding capabilities. While many ... -
Deep Pyramidal Residual Networks for Spectral-Spatial Hyperspectral Image Classification
Paoletti, Mercedes Eugenia; Haut, Juan M.; Fernandez-Beltran, Ruben; Plaza, Javier; Plaza, Antonio; Pla, Filiberto IEEE (2018-08)Convolutional neural networks (CNNs) exhibit good performance in image processing tasks, pointing themselves as the current state-of-the-art of deep learning methods. However, the intrinsic complexity of remotely sensed ... -
Deep Unsupervised Embedding for Remotely Sensed Images Based on Spatially Augmented Momentum Contrast
kang, jian; Fernandez-Beltran, Ruben; Duan, Puhong; Liu, Sicong; Plaza, Antonio IEEE (2020-07-14)Convolutional neural networks (CNNs) have achieved great success when characterizing remote sensing (RS) images. However, the lack of sufficient annotated data (together with the high complexity of the RS image domain) ... -
Efficient Implementation of Hyperspectral Anomaly Detection Techniques on GPUs and Multicore Processors
Molero, Jose M.; Garzon, E.M.; García, I.; Quintana-Orti, Enrique S.; Plaza, Antonio IEEE (2014)Anomaly detection is an important task for hyperspectral data exploitation. Although many algorithms have been developed for this purpose in recent years, due to the large dimensionality of hyperspectral image data, fast ... -
Endmember Extraction From Hyperspectral Imagery Based on Probabilistic Tensor Moments
Fernandez-Beltran, Ruben; Pla, Filiberto; Plaza, Antonio Institute of Electrical and Electronics Engineers (2020-01-13)This letter presents a novel hyperspectral endmember extraction approach that integrates a tensor-based decomposition scheme with a probabilistic framework in order to take advantage of both technologies when uncovering ... -
Exploring the performance–power–energy balance of low-power multicore and manycore architectures for anomaly detection in remote sensing
León Navarro, Germán; Molero, Jose M.; Garzon, E.M.; García, I.; Plaza, Antonio; Quintana-Orti, Enrique S. Springer Verlag (2015)In this paper, we perform an experimental study of the interactions between execution time (i.e., performance), power, and energy that occur in modern low-power architectures when executing the RX algorithm for detecting ... -
Fast and Reliable Noise Estimation for Hyperspectral Subspace Identification
Benner, Peter; Novaković, Vedran; Plaza, Antonio; Quintana-Orti, Enrique S. Institute of Electrical and Electronics Engineers (IEEE) (2015-02)In this letter, we introduce an efficient algorithm to estimate the noise correlation matrix in the initial stage of the hyperspectral signal identification by minimum error (HySime) method, commonly used for signal subspace ... -
Generalized Scalable Neighborhood Component Analysis for Single and Multi-Label Remote Sensing Image Characterization
kang, jian; SCARANO, Antonio; Plaza, Antonio IEEE (2021)Deep metric learning has recently become a prominent technology for the semantic understanding ofremote sensing (RS) scenes due to its great potential for characterizing visual semantics. However, state-of-the-art deep ... -
Graph Relation Network: Modeling Relations Between Scenes for Multilabel Remote-Sensing Image Classification and Retrieval
kang, jian; Fernandez-Beltran, Ruben; Danfeng, Hong; Chanussot, Jocelyn; Plaza, Antonio IEEE (2020-08-21)Due to the proliferation of large-scale remote-sensing (RS) archives with multiple annotations, multilabel RS scene classification and retrieval are becoming increasingly popular. Although some recent deep learning-based ... -
High-Rankness Regularized Semi-Supervised Deep Metric Learning for Remote Sensing Imagery
kang, jian; Fernandez-Beltran, Ruben; Ye, Zhen; Tong, Xiaohua; Ghamisi, Pedram; Plaza, Antonio MDPI (2020)Deep metric learning has recently received special attention in the field of remote sensing (RS) scene characterization, owing to its prominent capabilities for modeling distances among RS images based on their semantic ... -
Hyperspectral Unmixing Based on Dual-Depth Sparse Probabilistic Latent Semantic Analysis
Fernandez-Beltran, Ruben; Plaza, Antonio; Plaza, Javier; Pla, Filiberto IEEE (2018-06)This paper presents a novel approach for spectral unmixing of remotely sensed hyperspectral data. It exploits probabilistic latent topics in order to take advantage of the semantics pervading the latent topic space when ... -
Hyperspectral Unmixing on Multicore DSPs: Trading Off Performance for Energy
Castillo Catalán, María Isabel; Fernández Fernández, Juan Carlos; Igual, Francisco; Plaza, Antonio; Quintana-Orti, Enrique S.; Remón Gómez, Alfredo IEEE (2014)Wider coverage of observation missions will increase onboard power restrictions while, at the same time, pose higher demands from the perspective of processing time, thus asking for the exploration of novel high-performance ... -
Intersensor Remote Sensing Image Registration Using Multispectral Semantic Embeddings
Fernandez-Beltran, Ruben; Pla, Filiberto; Plaza, Antonio IEEE (2019-04)This letter presents a novel intersensor registration framework specially designed to register Sentinel-3 (S3) operational data using the Sentinel-2 (S2) instrument as a reference. The substantially higher resolution of ... -
Low-High-Power Consumption Architectures for Deep-Learning Models Applied to Hyperspectral Image Classification
Haut, Juan M.; Bernabé, Sergio; Paoletti, Mercedes Eugenia; Fernandez-Beltran, Ruben; Plaza, Antonio; Plaza, Javier IEEE (2018-11)Convolutional neural networks have emerged as an excellent tool for remotely sensed hyperspectral image (HSI) classification. Nonetheless, the high computational complexity and energy requirements of these models typically ... -
Multimodal Probabilistic Latent Semantic Analysis for Sentinel-1 and Sentinel-2 Image Fusion
Fernandez-Beltran, Ruben; Haut, Juan M.; Paoletti, Mercedes Eugenia; Plaza, Javier; Plaza, Antonio; Pla, Filiberto IEEE (2018-09)Probabilistic topic models have recently shown a great potential in the remote sensing image fusion field, which is particularly helpful in land-cover categorization tasks. This letter first studies the application of ... -
Noise-Tolerant Deep Neighborhood Embedding for Remotely Sensed Images With Label Noise
kang, jian; Fernandez-Beltran, Ruben; Kang, Xudong; Ni, Jingen; Plaza, Antonio IEEE (2021-02-02)Recently, many deep learning-based methods have been developed for solving remote sensing (RS) scene classification or retrieval tasks. Most of the adopted loss functions for training these models require accurate annotations. ...