SAR IMAGE ANALYSIS — A COMPUTATIONAL STATISTICS APPROACH Discover how to use statistics to extract information from SAR imageryIn SAR Image Analysis — A Computational Statistics Approach, an accomplished team of researchers delivers a practical exploration of how to use statistics to extract information from SAR imagery. The authors discuss various models, supply sample data and code, and explain theoretical aspects of SAR image analysis that are highly relevant to practitioners and students.The book offers the theoretical properties of models, estimators, interpretation, data visualization, and advanced techniques, along with the data and code samples, that students require to learn effectively and efficiently.SAR Image Analysis — A Computational Statistics Approach provides various exercises throughout the book to help readers reinforce and retain the extensive information on parameter estimation, applications, reproducibility, replicability, and advanced topics, like robust estimators and stochastic distances, contained within.The book also includes: Thorough introductions to data acquisition and the elements of data analysis and image processing with R, including useful R packages, preprocessing SAR data, and visualizationComprehensive explorations of intensity SAR data and the multiplicative model, including the (SAR) gamma distribution, the K distribution, the G0 distribution, and more general distributions under the multiplicative modelPractical discussions of parameter estimations, including the Bernoulli distribution, the negative binomial distribution, and the uniform distributionIn-depth examinations of applications, including statistical filters and classificationPerfect for undergraduate and graduate students studying remote sensing, data analysis, and statistics, SAR Image Analysis — A Computational Statistics Approach is also an indispensable resource for researchers, practitioners, and professionals seeking a one-stop resource on how to use statistics to extract information from SAR imagery.

SAR IMAGE ANALYSIS — A COMPUTATIONAL STATISTICS APPROACH

Discover how to use statistics to extract information from SAR imagery

In SAR Image Analysis — A Computational Statistics Approach, an accomplished team of researchers delivers a practical exploration of how to use statistics to extract information from SAR imagery. The authors discuss various models, supply sample data and code, and explain theoretical aspects of SAR image analysis that are highly relevant to practitioners and students.

The book offers the theoretical properties of models, estimators, interpretation, data visualization, and advanced techniques, along with the data and code samples, that students require to learn effectively and efficiently.

SAR Image Analysis — A Computational Statistics Approach provides various exercises throughout the book to help readers reinforce and retain the extensive information on parameter estimation, applications, reproducibility, replicability, and advanced topics, like robust estimators and stochastic distances, contained within.

The book also includes:

Thorough introductions to data acquisition and the elements of data analysis and image processing with R, including useful R packages, preprocessing SAR data, and visualization Comprehensive explorations of intensity SAR data and the multiplicative model, including the (SAR) gamma distribution, the K distribution, the G0 distribution, and more general distributions under the multiplicative model Practical discussions of parameter estimations, including the Bernoulli distribution, the negative binomial distribution, and the uniform distribution In-depth examinations of applications, including statistical filters and classification

Perfect for undergraduate and graduate students studying remote sensing, data analysis, and statistics, SAR Image Analysis — A Computational Statistics Approach is also an indispensable resource for researchers, practitioners, and professionals seeking a one-stop resource on how to use statistics to extract information from SAR imagery.

SAR IMAGE ANALYSIS — A COMPUTATIONAL STATISTICS APPROACH

Discover how to use statistics to extract information from SAR imagery

In SAR Image Analysis — A Computational Statistics Approach, an accomplished team of researchers delivers a practical exploration of how to use statistics to extract information from SAR imagery. The authors discuss various models, supply sample data and code, and explain theoretical aspects of SAR image analysis that are highly relevant to practitioners and students.

The book offers the theoretical properties of models, estimators, interpretation, data visualization, and advanced techniques, along with the data and code samples, that students require to learn effectively and efficiently.

SAR Image Analysis — A Computational Statistics Approach provides various exercises throughout the book to help readers reinforce and retain the extensive information on parameter estimation, applications, reproducibility, replicability, and advanced topics, like robust estimators and stochastic distances, contained within.

The book also includes:

Thorough introductions to data acquisition and the elements of data analysis and image processing with R, including useful R packages, preprocessing SAR data, and visualization Comprehensive explorations of intensity SAR data and the multiplicative model, including the (SAR) gamma distribution, the K distribution, the G0 distribution, and more general distributions under the multiplicative model Practical discussions of parameter estimations, including the Bernoulli distribution, the negative binomial distribution, and the uniform distribution In-depth examinations of applications, including statistical filters and classification

Perfect for undergraduate and graduate students studying remote sensing, data analysis, and statistics, SAR Image Analysis — A Computational Statistics Approach is also an indispensable resource for researchers, practitioners, and professionals seeking a one-stop resource on how to use statistics to extract information from SAR imagery.

This book constitutes the refereed proceedings of the 17th Iberoamerican Congress on Pattern Recognition, CIARP 2012, held in Buenos Aires, Argentina, in September 2012. The 109 papers presented, among them two tutorials and four keynotes, were carefully reviewed and selected from various submissions. The papers are organized in topical sections on face and iris: detection and recognition; clustering; fuzzy methods; human actions and gestures; graphs; image processing and analysis; shape and texture; learning, mining and neural networks; medical images; robotics, stereo vision and real time; remote sensing; signal processing; speech and handwriting analysis; statistical pattern recognition; theoretical pattern recognition; and video analysis.

This book constitutes the refereed proceedings of the 17th Iberoamerican Congress on Pattern Recognition, CIARP 2012, held in Buenos Aires, Argentina, in September 2012. The 109 papers presented, among them two tutorials and four keynotes, were carefully reviewed and selected from various submissions. The papers are organized in topical sections on face and iris: detection and recognition; clustering; fuzzy methods; human actions and gestures; graphs; image processing and analysis; shape and texture; learning, mining and neural networks; medical images; robotics, stereo vision and real time; remote sensing; signal processing; speech and handwriting analysis; statistical pattern recognition; theoretical pattern recognition; and video analysis.

El poder de los datos: ¿qué sucede cuando consulta, almacena o gestiona información?Las bases de datos son la columna vertebral de la era digital, pues permiten almacenar, gestionar y recuperar información de manera eficiente. Desde pequeños registros personales hasta sistemas que manejan grandes volúmenes de datos, estas tecnologías hacen posible el funcionamiento de aplicaciones, negocios y servicios online. Gracias a este libro, comprenderá los fundamentos del diseño, implementación y administración de bases de datos. A medida que avance en la lectura, aprenderá conceptos de forma progresiva, desde los fundamentos hasta niveles avanzados, con un enfoque práctico y el uso de múltiples herramientas de software libre. - Explorará los principales modelos de bases de datos y cómo se utilizan en distintos escenarios, desde sistemas relacionales hasta NoSQL. - Aprenderá a diseñar bases de datos eficientes, asegurando su integridad y optimización en el almacenamiento de datos. - Comprenderá cómo se estructuran y ejecutan las consultas SQL, dominando operaciones esenciales y avanzadas para la gestión de la información. - Descubrirá cómo integrar bases de datos con lenguajes de programación como Python, PHP y JavaScript, facilitando el desarrollo de aplicaciones dinámicas y escalables. - Utilizará herramientas de análisis y monitorización para optimizar el rendimiento y la fiabilidad de los sistemas de bases de datos. En la parte inferior de la primera página encontrará el código de acceso para descargar contenidos adicionales en www.marcombo.info, con recursos prácticos para reforzar su aprendizaje. Si es estudiante de ingeniería, profesional del sector o le apasiona el manejo de datos, este libro le proporcionará los conocimientos necesarios para comprender, diseñar y administrar bases de datos de manera efectiva, abriendo nuevas oportunidades académicas y profesionales.

SAR IMAGE ANALYSIS — A COMPUTATIONAL STATISTICS APPROACH Discover how to use statistics to extract information from SAR imageryIn SAR Image Analysis — A Computational Statistics Approach, an accomplished team of researchers delivers a practical exploration of how to use statistics to extract information from SAR imagery. The authors discuss various models, supply sample data and code, and explain theoretical aspects of SAR image analysis that are highly relevant to practitioners and students.The book offers the theoretical properties of models, estimators, interpretation, data visualization, and advanced techniques, along with the data and code samples, that students require to learn effectively and efficiently.SAR Image Analysis — A Computational Statistics Approach provides various exercises throughout the book to help readers reinforce and retain the extensive information on parameter estimation, applications, reproducibility, replicability, and advanced topics, like robust estimators and stochastic distances, contained within.The book also includes: Thorough introductions to data acquisition and the elements of data analysis and image processing with R, including useful R packages, preprocessing SAR data, and visualizationComprehensive explorations of intensity SAR data and the multiplicative model, including the (SAR) gamma distribution, the K distribution, the G0 distribution, and more general distributions under the multiplicative modelPractical discussions of parameter estimations, including the Bernoulli distribution, the negative binomial distribution, and the uniform distributionIn-depth examinations of applications, including statistical filters and classificationPerfect for undergraduate and graduate students studying remote sensing, data analysis, and statistics, SAR Image Analysis — A Computational Statistics Approach is also an indispensable resource for researchers, practitioners, and professionals seeking a one-stop resource on how to use statistics to extract information from SAR imagery.

SAR IMAGE ANALYSIS — A COMPUTATIONAL STATISTICS APPROACH

Discover how to use statistics to extract information from SAR imagery

In SAR Image Analysis — A Computational Statistics Approach, an accomplished team of researchers delivers a practical exploration of how to use statistics to extract information from SAR imagery. The authors discuss various models, supply sample data and code, and explain theoretical aspects of SAR image analysis that are highly relevant to practitioners and students.

The book offers the theoretical properties of models, estimators, interpretation, data visualization, and advanced techniques, along with the data and code samples, that students require to learn effectively and efficiently.

SAR Image Analysis — A Computational Statistics Approach provides various exercises throughout the book to help readers reinforce and retain the extensive information on parameter estimation, applications, reproducibility, replicability, and advanced topics, like robust estimators and stochastic distances, contained within.

The book also includes:

Thorough introductions to data acquisition and the elements of data analysis and image processing with R, including useful R packages, preprocessing SAR data, and visualization Comprehensive explorations of intensity SAR data and the multiplicative model, including the (SAR) gamma distribution, the K distribution, the G0 distribution, and more general distributions under the multiplicative model Practical discussions of parameter estimations, including the Bernoulli distribution, the negative binomial distribution, and the uniform distribution In-depth examinations of applications, including statistical filters and classification

Perfect for undergraduate and graduate students studying remote sensing, data analysis, and statistics, SAR Image Analysis — A Computational Statistics Approach is also an indispensable resource for researchers, practitioners, and professionals seeking a one-stop resource on how to use statistics to extract information from SAR imagery.

SAR IMAGE ANALYSIS — A COMPUTATIONAL STATISTICS APPROACH

Discover how to use statistics to extract information from SAR imagery

In SAR Image Analysis — A Computational Statistics Approach, an accomplished team of researchers delivers a practical exploration of how to use statistics to extract information from SAR imagery. The authors discuss various models, supply sample data and code, and explain theoretical aspects of SAR image analysis that are highly relevant to practitioners and students.

The book offers the theoretical properties of models, estimators, interpretation, data visualization, and advanced techniques, along with the data and code samples, that students require to learn effectively and efficiently.

SAR Image Analysis — A Computational Statistics Approach provides various exercises throughout the book to help readers reinforce and retain the extensive information on parameter estimation, applications, reproducibility, replicability, and advanced topics, like robust estimators and stochastic distances, contained within.

The book also includes:

Thorough introductions to data acquisition and the elements of data analysis and image processing with R, including useful R packages, preprocessing SAR data, and visualization Comprehensive explorations of intensity SAR data and the multiplicative model, including the (SAR) gamma distribution, the K distribution, the G0 distribution, and more general distributions under the multiplicative model Practical discussions of parameter estimations, including the Bernoulli distribution, the negative binomial distribution, and the uniform distribution In-depth examinations of applications, including statistical filters and classification

Perfect for undergraduate and graduate students studying remote sensing, data analysis, and statistics, SAR Image Analysis — A Computational Statistics Approach is also an indispensable resource for researchers, practitioners, and professionals seeking a one-stop resource on how to use statistics to extract information from SAR imagery.

This book constitutes the refereed proceedings of the 17th Iberoamerican Congress on Pattern Recognition, CIARP 2012, held in Buenos Aires, Argentina, in September 2012. The 109 papers presented, among them two tutorials and four keynotes, were carefully reviewed and selected from various submissions. The papers are organized in topical sections on face and iris: detection and recognition; clustering; fuzzy methods; human actions and gestures; graphs; image processing and analysis; shape and texture; learning, mining and neural networks; medical images; robotics, stereo vision and real time; remote sensing; signal processing; speech and handwriting analysis; statistical pattern recognition; theoretical pattern recognition; and video analysis.

This book constitutes the refereed proceedings of the 17th Iberoamerican Congress on Pattern Recognition, CIARP 2012, held in Buenos Aires, Argentina, in September 2012. The 109 papers presented, among them two tutorials and four keynotes, were carefully reviewed and selected from various submissions. The papers are organized in topical sections on face and iris: detection and recognition; clustering; fuzzy methods; human actions and gestures; graphs; image processing and analysis; shape and texture; learning, mining and neural networks; medical images; robotics, stereo vision and real time; remote sensing; signal processing; speech and handwriting analysis; statistical pattern recognition; theoretical pattern recognition; and video analysis.

El poder de los datos: ¿qué sucede cuando consulta, almacena o gestiona información?Las bases de datos son la columna vertebral de la era digital, pues permiten almacenar, gestionar y recuperar información de manera eficiente. Desde pequeños registros personales hasta sistemas que manejan grandes volúmenes de datos, estas tecnologías hacen posible el funcionamiento de aplicaciones, negocios y servicios online. Gracias a este libro, comprenderá los fundamentos del diseño, implementación y administración de bases de datos. A medida que avance en la lectura, aprenderá conceptos de forma progresiva, desde los fundamentos hasta niveles avanzados, con un enfoque práctico y el uso de múltiples herramientas de software libre. - Explorará los principales modelos de bases de datos y cómo se utilizan en distintos escenarios, desde sistemas relacionales hasta NoSQL. - Aprenderá a diseñar bases de datos eficientes, asegurando su integridad y optimización en el almacenamiento de datos. - Comprenderá cómo se estructuran y ejecutan las consultas SQL, dominando operaciones esenciales y avanzadas para la gestión de la información. - Descubrirá cómo integrar bases de datos con lenguajes de programación como Python, PHP y JavaScript, facilitando el desarrollo de aplicaciones dinámicas y escalables. - Utilizará herramientas de análisis y monitorización para optimizar el rendimiento y la fiabilidad de los sistemas de bases de datos. En la parte inferior de la primera página encontrará el código de acceso para descargar contenidos adicionales en www.marcombo.info, con recursos prácticos para reforzar su aprendizaje. Si es estudiante de ingeniería, profesional del sector o le apasiona el manejo de datos, este libro le proporcionará los conocimientos necesarios para comprender, diseñar y administrar bases de datos de manera efectiva, abriendo nuevas oportunidades académicas y profesionales.