In recent years, there have been significant progress in computational intelligence and image processing with machine learning and deep learning as important components of modern artificial intelligence. All these progresses face challenges in dealing with Covid-19 pandemic for detection and treatment.This comprehensive compendium provides not only updated advances of computational intelligence and image processing in the detection and treatment of Covid-19, but also other medical applications such as in cancer detection and cardiovascular diseases, etc. More traditional approaches such as 2D segmentation and 3D reconstruction are included.The useful reference text is an updated version of the edited title, Computer Vision in Medical Imaging (World Scientific, 2014) and its companion volume, Frontiers of Medical Imaging (World Scientific, 2015). The book is written for engineers, scientists and the medical community to meet the increased challenges in medical applications.

This compendium provides a hands-on description of Random Forests. It starts with a consistent introduction of general methods to create, train, and fuse ensembles of decision trees. Instead of limiting the discussion to the general-purpose layout of traditional Random Forests, this book outlines specifications during tree creation and training that are especially well suited to analyze structured data such as images. The theoretical foundations are explained as well as practical and implementation issues. The many possible variations of the Random Forest model are discussed together with their implications on the prediction results to provide insights into the influence of these parameters and their possible side-effects. Last but not least, this unique title provides specific examples of the usage of Random Forests for analysing remote sensing imagery.

This invaluable compendium highlights the challenges of perioperative process in hospitals today. It delves into the development of a multi-agent robotic system where a dirty-side robot that sorts instruments returned from a surgical room into different containers for easy scrubbing, a Traybot that navigates the environment and transports the instrument containers to different stations, a clean-side robot that picks up instruments and places them in surgical kits, and an orchestration software architecture that manages the cooperation between different robots.The book discusses the technical details of all the components, from system architecture to the details of the end-effector design. Readers will gain significant knowledge on how such a system was put together.Related Link(s);

This unique compendium presents the major methods of recognition and learning used in syntactic pattern recognition from the 1960s till 2018. Each method is introduced firstly in a formal way. Then, it is explained with the help of examples and its algorithms are described in a pseudocode. The survey of the applications contains more than 1,000 sources published since the 1960s. The open problems in the field, the challenges and the determinants of the future development of syntactic pattern recognition are discussed.This must-have volume provides a good read and serves as an excellent source of reference materials for researchers, academics, and postgraduate students in the fields of pattern recognition, machine perception, computer vision and artificial intelligence.

This book gives a comprehensive overview of the most advanced theories, methodologies and applications in computer vision. Particularly, it gives an extensive coverage of 3D and robotic vision problems. Example chapters featured are Fourier methods for 3D surface modeling and analysis, use of constraints for calibration-free 3D Euclidean reconstruction, novel photogeometric methods for capturing static and dynamic objects, performance evaluation of robot localization methods in outdoor terrains, integrating 3D vision with force/tactile sensors, tracking via in-floor sensing, self-calibration of camera networks, etc. Some unique applications of computer vision in marine fishery, biomedical issues, driver assistance, are also highlighted.

The major progress in computer vision allows us to make extensive use of medical imaging data to provide us better diagnosis, treatment and predication of diseases. Computer vision can exploit texture, shape, contour and prior knowledge along with contextual information from image sequence and provide 3D and 4D information that helps with better human understanding. Many powerful tools have been available through image segmentation, machine learning, pattern classification, tracking, reconstruction to bring much needed quantitative information not easily available by trained human specialists. The aim of the book is for both medical imaging professionals to acquire and interpret the data, and computer vision professionals to provide enhanced medical information by using computer vision techniques. The final objective is to benefit the patients without adding to the already high medical costs.

The book presents a collection of practical applications of image processing and analysis. Different vision systems are more often used among others in the automotive industry, pharmacy, military and police equipment, automated production and measurement systems. In each of these fields of technology, digital image processing and analysis module is a critical part of the process of building this type of system. The majority of books in the market deal with theoretical issues. However, this unique publication specially highlights industrial applications, especially industrial measurement applications. Along with its wide spectrum of image processing and analysis applications, this book is an interesting reference for both students and professionals.

The main subject of the monograph is the fractional calculus in the discrete version. The volume is divided into three main parts. Part one contains a theoretical introduction to the classical and fractional-order discrete calculus where the fundamental role is played by the backward difference and sum. In the second part, selected applications of the discrete fractional calculus in the discrete system control theory are presented. In the discrete system identification, analysis and synthesis, one can consider integer or fractional models based on the fractional-order difference equations. The third part of the book is devoted to digital image processing.

In recent years, there have been significant progress in computational intelligence and image processing with machine learning and deep learning as important components of modern artificial intelligence. All these progresses face challenges in dealing with Covid-19 pandemic for detection and treatment.This comprehensive compendium provides not only updated advances of computational intelligence and image processing in the detection and treatment of Covid-19, but also other medical applications such as in cancer detection and cardiovascular diseases, etc. More traditional approaches such as 2D segmentation and 3D reconstruction are included.The useful reference text is an updated version of the edited title, Computer Vision in Medical Imaging (World Scientific, 2014) and its companion volume, Frontiers of Medical Imaging (World Scientific, 2015). The book is written for engineers, scientists and the medical community to meet the increased challenges in medical applications.

This compendium provides a hands-on description of Random Forests. It starts with a consistent introduction of general methods to create, train, and fuse ensembles of decision trees. Instead of limiting the discussion to the general-purpose layout of traditional Random Forests, this book outlines specifications during tree creation and training that are especially well suited to analyze structured data such as images. The theoretical foundations are explained as well as practical and implementation issues. The many possible variations of the Random Forest model are discussed together with their implications on the prediction results to provide insights into the influence of these parameters and their possible side-effects. Last but not least, this unique title provides specific examples of the usage of Random Forests for analysing remote sensing imagery.

This invaluable compendium highlights the challenges of perioperative process in hospitals today. It delves into the development of a multi-agent robotic system where a dirty-side robot that sorts instruments returned from a surgical room into different containers for easy scrubbing, a Traybot that navigates the environment and transports the instrument containers to different stations, a clean-side robot that picks up instruments and places them in surgical kits, and an orchestration software architecture that manages the cooperation between different robots.The book discusses the technical details of all the components, from system architecture to the details of the end-effector design. Readers will gain significant knowledge on how such a system was put together.Related Link(s);

This unique compendium presents the major methods of recognition and learning used in syntactic pattern recognition from the 1960s till 2018. Each method is introduced firstly in a formal way. Then, it is explained with the help of examples and its algorithms are described in a pseudocode. The survey of the applications contains more than 1,000 sources published since the 1960s. The open problems in the field, the challenges and the determinants of the future development of syntactic pattern recognition are discussed.This must-have volume provides a good read and serves as an excellent source of reference materials for researchers, academics, and postgraduate students in the fields of pattern recognition, machine perception, computer vision and artificial intelligence.

This book gives a comprehensive overview of the most advanced theories, methodologies and applications in computer vision. Particularly, it gives an extensive coverage of 3D and robotic vision problems. Example chapters featured are Fourier methods for 3D surface modeling and analysis, use of constraints for calibration-free 3D Euclidean reconstruction, novel photogeometric methods for capturing static and dynamic objects, performance evaluation of robot localization methods in outdoor terrains, integrating 3D vision with force/tactile sensors, tracking via in-floor sensing, self-calibration of camera networks, etc. Some unique applications of computer vision in marine fishery, biomedical issues, driver assistance, are also highlighted.

The major progress in computer vision allows us to make extensive use of medical imaging data to provide us better diagnosis, treatment and predication of diseases. Computer vision can exploit texture, shape, contour and prior knowledge along with contextual information from image sequence and provide 3D and 4D information that helps with better human understanding. Many powerful tools have been available through image segmentation, machine learning, pattern classification, tracking, reconstruction to bring much needed quantitative information not easily available by trained human specialists. The aim of the book is for both medical imaging professionals to acquire and interpret the data, and computer vision professionals to provide enhanced medical information by using computer vision techniques. The final objective is to benefit the patients without adding to the already high medical costs.

The book presents a collection of practical applications of image processing and analysis. Different vision systems are more often used among others in the automotive industry, pharmacy, military and police equipment, automated production and measurement systems. In each of these fields of technology, digital image processing and analysis module is a critical part of the process of building this type of system. The majority of books in the market deal with theoretical issues. However, this unique publication specially highlights industrial applications, especially industrial measurement applications. Along with its wide spectrum of image processing and analysis applications, this book is an interesting reference for both students and professionals.

The main subject of the monograph is the fractional calculus in the discrete version. The volume is divided into three main parts. Part one contains a theoretical introduction to the classical and fractional-order discrete calculus where the fundamental role is played by the backward difference and sum. In the second part, selected applications of the discrete fractional calculus in the discrete system control theory are presented. In the discrete system identification, analysis and synthesis, one can consider integer or fractional models based on the fractional-order difference equations. The third part of the book is devoted to digital image processing.