Geomatics Program Expert Session

04.30 PM - 06.00 PM

FT-216 (Faculty of Technology, CEPT University), CEPT University, Ahmedabad.

Open For All.

2019-06-27 16:30:00 2019-06-27 18:00:00 Asia/Kolkata Geomatics Program Expert Session

Geomatics Program Expert Session
Jointly organized by
IEEE GRSS (Gujarat Chapter)

Machine Learning for Remote Sensing Data Analysis
Speaker: Dr. Gustau Camps-Valls

Machine learning has become a standard paradigm for the analysis of remote sensing and geoscience data at both local and global scales. In the upcoming years, with the advent of new satellite constellations, machine learning will have a fundamental role in processing large and heterogeneous data sources. Machine learning will move from mere statistical data processing to actual learning, understanding, and knowledge extraction. The ambitious goal is to provide responses to the challenging scientific questions about the Earth system.

The current lecture shall be focused on remote sensing image processing chain, and take the attendants on a tour of different strategies for feature extraction, classification, unmixing, retrieval, and pattern analysis for remote sensing data analysis. Powerful methodologies for remote sensing supervised remote sensing data classification shall be discussed: extracting knowledge from data, including interactive approaches via active learning, classifiers that encode prior knowledge and invariances, semi supervised learning that exploit the information of unlabelled data, and domain adaptation to compensate for shifts in the ever-changing data distributions. Latest advances in the field of unmixing will be reviewed, covering sparse approaches, spatial-spectral methods, and methods constrained by physical models. Finally, recent advances in bio-geophysical parameter estimation that care about remote sensing data characteristics, such as spatial and temporal structures or the presence of heteroscedastic noise shall be covered. Beyond theory, results of recent studies illustrating all the covered issues will be presented.

About Speaker
Gustau Camps-Valls (IEEE Member’04, IEEE Senior Member’07) received a B.Sc. degree in Physics (1996), in Electronics Engineering (1998), and a Ph.D. degree in Physics (2002) all from the Universitat de València. He is currently an Associate Professor (hab. Full professor) in the Department of Electronics Engineering. He is a research coordinator in the Image and Signal Processing (ISP) group. He has been a Visiting Researcher at the Remote Sensing Laboratory (Univ. Trento, Italy) in 2002, the Max Planck Institute for Biological Cybernetics (Tübingen, Germany) in 2009, and was invited as Professor at the Laboratory of Geographic Information Systems of the École Polytechnique Fédérale de Lausanne (Lausanne, Switzerland) in 2013.

He is interested in the development of machine learning algorithms for geoscience and remote sensing data analysis. He is an author of 130 journal papers, more than 150 conference papers, 20 international book chapters, and editor of the books “Kernel methods in bioengineering, signal and image processing” (IGI, 2007), “Kernel methods for Remote Sensing data analysis” (Wiley & Sons, 2009), and “Remote Sensing Image Processing” (MC, 2011).

Source: Facebook.

FT-216 (Faculty of Technology, CEPT University), CEPT University, Ahmedabad.

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Geomatics Program Expert Session
Jointly organized by
IEEE GRSS (Gujarat Chapter)

Machine Learning for Remote Sensing Data Analysis
Speaker: Dr. Gustau Camps-Valls

Machine learning has become a standard paradigm for the analysis of remote sensing and geoscience data at both local and global scales. In the upcoming years, with the advent of new satellite constellations, machine learning will have a fundamental role in processing large and heterogeneous data sources. Machine learning will move from mere statistical data processing to actual learning, understanding, and knowledge extraction. The ambitious goal is to provide responses to the challenging scientific questions about the Earth system.

The current lecture shall be focused on remote sensing image processing chain, and take the attendants on a tour of different strategies for feature extraction, classification, unmixing, retrieval, and pattern analysis for remote sensing data analysis. Powerful methodologies for remote sensing supervised remote sensing data classification shall be discussed: extracting knowledge from data, including interactive approaches via active learning, classifiers that encode prior knowledge and invariances, semi supervised learning that exploit the information of unlabelled data, and domain adaptation to compensate for shifts in the ever-changing data distributions. Latest advances in the field of unmixing will be reviewed, covering sparse approaches, spatial-spectral methods, and methods constrained by physical models. Finally, recent advances in bio-geophysical parameter estimation that care about remote sensing data characteristics, such as spatial and temporal structures or the presence of heteroscedastic noise shall be covered. Beyond theory, results of recent studies illustrating all the covered issues will be presented.

About Speaker
Gustau Camps-Valls (IEEE Member’04, IEEE Senior Member’07) received a B.Sc. degree in Physics (1996), in Electronics Engineering (1998), and a Ph.D. degree in Physics (2002) all from the Universitat de València. He is currently an Associate Professor (hab. Full professor) in the Department of Electronics Engineering. He is a research coordinator in the Image and Signal Processing (ISP) group. He has been a Visiting Researcher at the Remote Sensing Laboratory (Univ. Trento, Italy) in 2002, the Max Planck Institute for Biological Cybernetics (Tübingen, Germany) in 2009, and was invited as Professor at the Laboratory of Geographic Information Systems of the École Polytechnique Fédérale de Lausanne (Lausanne, Switzerland) in 2013.

He is interested in the development of machine learning algorithms for geoscience and remote sensing data analysis. He is an author of 130 journal papers, more than 150 conference papers, 20 international book chapters, and editor of the books “Kernel methods in bioengineering, signal and image processing” (IGI, 2007), “Kernel methods for Remote Sensing data analysis” (Wiley & Sons, 2009), and “Remote Sensing Image Processing” (MC, 2011).

Source: Facebook.




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