2018 - IEEE Fellow For contributions to machine learning in remote sensing
His primary scientific interests are in Artificial intelligence, Hyperspectral imaging, Support vector machine, Pattern recognition and Remote sensing. His study in Artificial intelligence is interdisciplinary in nature, drawing from both Machine learning and Big data. His work in the fields of HyMap overlaps with other areas such as Complex data type.
His work on Kernel method and Radial basis function kernel is typically connected to Nonlinear system identification as part of general Support vector machine study, connecting several disciplines of science. Many of his studies involve connections with topics such as Contextual image classification and Pattern recognition. His Remote sensing research is multidisciplinary, relying on both Regression analysis, Data mining and Vegetation.
Gustau Camps-Valls focuses on Artificial intelligence, Remote sensing, Pattern recognition, Support vector machine and Gaussian process. The Artificial intelligence study combines topics in areas such as Machine learning and Computer vision. When carried out as part of a general Remote sensing research project, his work on Multispectral image is frequently linked to work in Environmental science, therefore connecting diverse disciplines of study.
His Pattern recognition research incorporates themes from Data mining and Robustness. His Support vector machine study integrates concerns from other disciplines, such as Artificial neural network and Pixel. His Contextual image classification study frequently draws parallels with other fields, such as Kernel.
Gustau Camps-Valls mainly investigates Environmental science, Gaussian process, Artificial intelligence, Remote sensing and Earth observation. His Artificial intelligence research is multidisciplinary, incorporating perspectives in Mesoscale meteorology, Machine learning, Crop yield and Pattern recognition. He is studying Dimensionality reduction, which is a component of Pattern recognition.
His studies deal with areas such as Mean squared error, Feature, Artificial neural network and Sensor fusion as well as Remote sensing. His Earth observation research includes themes of Nonlinear system, Data mining and Spatial variability. Gustau Camps-Valls has included themes like Random variable, Support vector machine and Consistency in his Theoretical computer science study.
His scientific interests lie mostly in Remote sensing, Environmental science, Earth observation, Gaussian process and Earth system science. Gustau Camps-Valls focuses mostly in the field of Remote sensing, narrowing it down to matters related to Sensor fusion and, in some cases, Image resolution, Smoothing and Multispectral image. As a part of the same scientific family, Gustau Camps-Valls mostly works in the field of Earth observation, focusing on Data mining and, on occasion, Parametric statistics.
His Earth system science study incorporates themes from Dependency, Curse of dimensionality and Data science. The concepts of his Mean squared error study are interwoven with issues in Hyperspectral imaging, Heteroscedasticity, Leaf area index, Cluster analysis and Synthetic aperture radar. His research on Artificial intelligence focuses in particular on Data-driven.
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Kernel-based methods for hyperspectral image classification
G. Camps-Valls;L. Bruzzone.
IEEE Transactions on Geoscience and Remote Sensing (2005)
Composite kernels for hyperspectral image classification
G. Camps-Valls;L. Gomez-Chova;J. Munoz-Mari;J. Vila-Frances.
IEEE Geoscience and Remote Sensing Letters (2006)
Hyperspectral Remote Sensing Data Analysis and Future Challenges
J. M. Bioucas-Dias;A. Plaza;G. Camps-Valls;P. Scheunders.
IEEE Geoscience and Remote Sensing Magazine (2013)
Deep learning and process understanding for data-driven Earth system science
Markus Reichstein;Gustau Camps-Valls;Bjorn Stevens;Martin Jung.
Unsupervised Deep Feature Extraction for Remote Sensing Image Classification
Adriana Romero;Carlo Gatta;Gustau Camps-Valls.
IEEE Transactions on Geoscience and Remote Sensing (2016)
Classification of Hyperspectral Images With Regularized Linear Discriminant Analysis
T.V. Bandos;L. Bruzzone;G. Camps-Valls.
IEEE Transactions on Geoscience and Remote Sensing (2009)
Kernel-Based Framework for Multitemporal and Multisource Remote Sensing Data Classification and Change Detection
G. Camps-Valls;L. Gomez-Chova;J. Munoz-Mari;J.L. Rojo-Alvarez.
IEEE Transactions on Geoscience and Remote Sensing (2008)
Optical remote sensing and the retrieval of terrestrial vegetation bio-geophysical properties - A review
Jochem Verrelst;Gustau Camps-Valls;Jordi Muñoz-Marí;Juan Pablo Rivera.
Isprs Journal of Photogrammetry and Remote Sensing (2015)
Robust support vector method for hyperspectral data classification and knowledge discovery
G. Camps-Valls;L. Gomez-Chova;J. Calpe-Maravilla;J.D. Martin-Guerrero.
IEEE Transactions on Geoscience and Remote Sensing (2004)
Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms
Gianluca Tramontana;Martin Jung;Christopher R. Schwalm;Kazuhito Ichii.
Profile was last updated on December 6th, 2021.
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