Visualitza Institute of New Imaging Technologies (INIT) per autoria "c5f1b887-d60c-4409-97c8-a6c54141a0dd"
Ara mostrant els elements 1-9 d 9
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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 ... -
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 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 ... -
GPU Parallel Implementation of Dual-Depth Sparse Probabilistic Latent Semantic Analysis for Hyperspectral Unmixing
Gallardo Jaramago, Jose Antonio; Paoletti, Mercedes Eugenia; Haut, Juan M.; Fernandez-Beltran, Ruben IEEE (2019-08-22)Hyperspectral unmixing (HU) is an important task for remotely sensed hyperspectral (HS) data exploitation. It comprises the identification of pure spectral signatures (endmembers) and their corresponding fractional abundances ... -
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 ... -
Remote Sensing Image Fusion Using Hierarchical Multimodal Probabilistic Latent Semantic Analysis
Fernandez-Beltran, Ruben; Haut, Juan M.; Paoletti, Mercedes Eugenia; Plaza, Javier; Plaza, Antonio; Pla, Filiberto IEEE (2018-11)The generative semantic nature of probabilistic topic models has recently shown encouraging results within the remote sensing image fusion field when conducting land cover categorization. However, standard topic models ... -
Remote Sensing Image Superresolution Using Deep Residual Channel Attention
Haut, Juan M.; Fernandez-Beltran, Ruben; Paoletti, Mercedes Eugenia; Plaza, Javier; Plaza, Antonio IEEE (2019-07-23)The current trend in remote sensing image superresolution (SR) is to use supervised deep learning models to effectively enhance the spatial resolution of airborne and satellite-based optical imagery. Nonetheless, the ... -
Remote Sensing Single-Image Superresolution Based on a Deep Compendium Model
Haut, Juan M.; Paoletti, Mercedes Eugenia; Fernandez-Beltran, Ruben; Plaza, Javier; Plaza, Antonio; Li, Jun IEEE (2019-03)This letter introduces a novel remote sensing single-image superresolution (SR) architecture based on a deep efficient compendium model. The current deep learning-based SR trend stands for using deeper networks to improve ...