3D printing Aerodynamic engineering Aeronautical engineering Aeronautical engineering books Airports Architecture Artificial intelligence Automobiles Blast Resistant Design Books Bridges Building Codes Cabin Systems Civil Engineering Codes Concrete Conferences Construction Management Construction Materials Cooling Cryptocurrency Dams Do it Yourself Docks and Harbours Downloads Earthquake Engineering Electronics Engineering Engines Environmental Design & Construction Environmental Engineering Estimation Fluid Mechanics Fluid Mechanics Books Formwork design foundation engineering General Geotech Books Geotechnical Engineering Global Positioning System HVAC Hydraulics Hydraulics Books Hydro Power Hydrology Irrigation Engineering Machinery Magazines Management Books Masonry Mechanical Engineering Mechanics Mechanics Books Miscellaneous Books Modern Steel Construction Nanotechnology Natural Hazards Network Security Engineer Networking Systems News Noise and Attenuation Nuclear Engineering Nuclear Hazards to Buildings Pavement Design Prestressed Concrete Project Management Project Management Books Quantity Survey Quantity Survey Books railways RCC Structural Designing Remote Sensing Remote Sensing and GIS Books Renewable Energy Reports Resume Roads scholarships Smart devices Software Software Engineering Soil Mechanics Solar Energy Special Concrete Spreadsheets Steel Steel Spreadsheets Structural Analyses structures Structures Books Surveying Surveying Books Testing Thermodynamics Thesis Transportation Books Transportation Engineering Tunnel Engineering Wind Energy Zero Energy Buildings

Book: Kernel Methods for Remote Sensing Data Analysis by Gustavo Camps-Valls, Lorenzo Bruzzone

Book: Kernel Methods for Remote Sensing Data Analysis by Gustavo Camps-Valls, Lorenzo Bruzzone
Machine learning experienced a great advance in the 1980s and 1990s due to the active research in artificial neural networks, adaptive schemes and fuzzy systems. These methodologies demonstrated good results in many real applications, especially for classification and regression tasks, since neither a priori knowledge about the model of the distribution of the available data nor the relationships among the independent variables should be necessarily assumed. These desirable properties are at the basis of the success of these methods in the field of the analysis of remote sensing images, where a wide literature refers to the definition of classifiers and estimation algorithms based on neural networks and fuzzy systems.

Author Name


Contact Form


Email *

Message *

Powered by Blogger.