Listar por tema "remote sensing"

Mostrando ítems 1-17 de 17

    • openAccess   A high-resolution, integrated system for rice yield forecasting at district level 

      Pagani, Valentina; Guarneri, Tommaso; Busetto, Lorenzo; Ranghetti, Luigi; BOSCHETTI, MIRCO; Movedi, Ermes; Campos-Taberner, Manuel; García Haro, Francisco Javier; Katsantonis, Dimitrios; Stavrakoudis, Dimitris; Ricciardelli, Elisabetta; Romano, Filomena; Holecz, Francesco; Collivignarelli, Francesco; Granell, Carlos; Casteleyn, Sven; Confalonieri, Roberto Elsevier Masson (2019-01)
      To meet the growing demands from public and private stakeholders for early yield estimates, a high-resolution (2 km × 2 km) rice yield forecasting system based on the integration of the WARM model and remote sensing (RS) ...

    • openAccess   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 ...

    • openAccess   Deep Hashing Based on Class-Discriminated Neighborhood Embedding 

      kang, jian; Fernandez-Beltran, Ruben; Zhen, Ye; Tong, Xiaohua Institute of Electrical and Electronics Engineers (2020-09-30)
      Deep-hashing methods have drawn significant attention during the past years in the field of remote sensing (RS) owing to their prominent capabilities for capturing the semantics from complex RS scenes and generating the ...

    • openAccess   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) ...

    • openAccess   Downstream Services for Rice Crop Monitoring in Europe: From Regional to Local Scale 

      Busetto, Lorenzo; Casteleyn, Sven; Granell, Carlos; Pepe, Monica; Barbieri, Massimo; Campos-Taberner, Manuel; CASA, Raffaele; Collivignarelli, Francesco; Confalonieri, Roberto; Crema, Alberto; García Haro, Francisco Javier; Luca Gatti; Gatti, Luca; Gitas, Ioannis; González-Pérez, Alberto; Grau Muedra, Gonçal Andreu; Guarneri, Tommaso; Holecz, Francesco; Katsantonis, Dimitrios; Minakou, Chara; Miralles, Ignacio; Movedi, Ermes; Nutini, Francesco; Pagani, Valentina; Palombo, Angelo; DI Paola, Francesco; Pascucci, Simone; Pignatti, Stefano; RAMPINI, ANNA; Ranghetti, Luigi; Ricciardelli, Elisabetta; Romano, Filomena; Stavrakoudis, Dimitris; STROPPIANA, DANIELA; VIGGIANO, MARIASSUNTA; BOSCHETTI, MIRCO Institute of Electrical and Electronics Engineers (IEEE) (2017-04)
      The ERMES agromonitoring system for rice cultivations integrates EO data at different resolutions, crop models, and user-provided in situ data in a unified system, which drives two operational downstream services for rice ...

    • closedAccess   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 ...

    • openAccess   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 ...

    • openAccess   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 ...

    • openAccess   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 ...

    • openAccess   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 ...

    • openAccess   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 ...

    • openAccess   Remotely Sensed Data Fusion for Spatiotemporal Geostatistical Analysis of Forest Fire Hazard 

      Sakellariou, Stavros; Cabral, Pedro; Caetano, Mario; Pla, Filiberto; Painho, Marco; Christopoulou, Olga; Sfougaris, Athanassios; Dalezios, Nicolas; Vasilakos, Christos MDPI (2020)
      Forest fires are a natural phenomenon which might have severe implications on naturaland anthropogenic ecosystems. Future projections predict that, under a climate change environment,the fire season would be lengthier with ...

    • closedAccess   SEN23E: A Cloudless Geo-Referenced Multi-Spectral Sentinel-2/Sentinel-3 Dataset for Data Fusion Analysis 

      Ibáñez Fernández, Damián; Fernandez-Beltran, Ruben; Pla, Filiberto IEEE (2022-07)
      The availability of geo-referenced coupled data of dif-ferent platforms is essential to train remote sensing (RS) multi-modal classification and bio-phyiscal parameter esti-mation learning methods. To properly develop a ...

    • openAccess   Teledetecció en Arqueologia. Noves aportacions a la topografia de l’oppidum ibèric de la Balaguera (la Pobla Tornesa, Castelló) a través de les dades LIDAR 

      Mateu Pitarch, Raül Servei d’Investigacions Arqueològiques i Prehistòriques (2020)
      Con este estudio se pretende realizar una propuesta de revisión de anteriores estudios sobre el oppidum ibérico del Tossal de la Balaguera. Mediante la teledetección se revisaran aspectos como su extensión, además de otros ...

    • openAccess   Transfer Deep Learning for Remote Sensing Datasets: A Comparison Study 

      Hernandez-Sequeira, Itza; Fernandez-Beltran, Ruben; Pla, Filiberto IEEE (2022-07-17)
      Remote sensing is also benefiting from the quick development of deep learning algorithms for image analysis and classification tasks. In this paper, we evaluate the classification performance of a well-known Convolutional ...

    • openAccess   Unsupervised Remote Sensing Image Retrieval Using Probabilistic Latent Semantic Hashing 

      Fernandez-Beltran, Ruben; Demir, Begüm; Pla, Filiberto; Plaza, Antonio Institute of Electrical and Electronics Engineers (2020-02-06)
      Unsupervised hashing methods have attracted considerable attention in large-scale remote sensing (RS) image retrieval, due to their capability for massive data processing with significantly reduced storage and computation. ...

    • openAccess   W-NetPan: Double-U network for inter-sensor self-supervised pan-sharpening 

      Fernandez-Beltran, Ruben; Fernandez-Botran, Rafael; kang, jian; Pla, Filiberto Elsevier ScienceDirect (2023-02-08)
      The increasing availability of remote sensing data allows dealing with spatial-spectral limitations by means of pan-sharpening methods. However, fusing inter-sensor data poses important challenges, in terms of resolution ...