Isabelle Bloch – författare

The area of information fusion has grown considerably during the last few years, leading to a rapid and impressive evolution. In such fast-moving times, it is important to take stock of the changes that have occurred. As such, this books offers an overview of the general principles and specificities of information fusion in signal and image processing, as well as covering the main numerical methods (probabilistic approaches, fuzzy sets and possibility theory and belief functions).

The area of information fusion has grown considerably during the last few years, leading to a rapid and impressive evolution. In such fast-moving times, it is important to take stock of the changes that have occurred. As such, this books offers an overview of the general principles and specificities of information fusion in signal and image processing, as well as covering the main numerical methods (probabilistic approaches, fuzzy sets and possibility theory and belief functions).

The area of information fusion has grown considerably during the last few years, leading to a rapid and impressive evolution. In such fast-moving times, it is important to take stock of the changes that have occurred. As such, this books offers an overview of the general principles and specificities of information fusion in signal and image processing, as well as covering the main numerical methods (probabilistic approaches, fuzzy sets and possibility theory and belief functions).

This book constitutes the refereed proceedings of the 7th International Conference on Belief Functions, BELIEF 2022, held in Paris, France, in October 2022.The theory of belief functions is now well established as a general framework for reasoning with uncertainty, and has well-understood connections to other frameworks such as probability, possibility, and imprecise probability theories. It has been applied in diverse areas such as machine learning, information fusion, and pattern recognition.The 29 full papers presented in this book were carefully selected and reviewed from 31 submissions. The papers cover a wide range on theoretical aspects on mathematical foundations, statistical inference as well as on applications in various areas including classification, clustering, data fusion, image processing, and much more.

This book constitutes the refereed proceedings of the 7th International Conference on Belief Functions, BELIEF 2022, held in Paris, France, in October 2022.

The theory of belief functions is now well established as a general framework for reasoning with uncertainty, and has well-understood connections to other frameworks such as probability, possibility, and imprecise probability theories. It has been applied in diverse areas such as machine learning, information fusion, and pattern recognition.

The 29 full papers presented in this book were carefully selected and reviewed from 31 submissions. The papers cover a wide range on theoretical aspects on mathematical foundations, statistical inference as well as on applications in various areas including classification, clustering, data fusion, image processing, and much more.

This book provides a thorough overview of recent methods using higher level information (object or scene level) for advanced tasks such as image understanding along with their applications to medical images. Advanced methods for fuzzy image processing and understanding are presented, including fuzzy spatial objects, geometry and topology, mathematical morphology, machine learning, verbal descriptions of image content, fusion, spatial relations, and structural representations. For each methodological aspect covered, illustrations from the medical imaging domain are provided. This is an ideal book for graduate students and researchers in the field of medical image processing.

This book provides a thorough overview of recent methods using higher level information (object or scene level) for advanced tasks such as image understanding along with their applications to medical images. Advanced methods for fuzzy image processing and understanding are presented, including fuzzy spatial objects, geometry and topology, mathematical morphology, machine learning, verbal descriptions of image content, fusion, spatial relations, and structural representations. For each methodological aspect covered, illustrations from the medical imaging domain are provided. This is an ideal book for graduate students and researchers in the field of medical image processing.

This book provides a thorough overview of recent methods using higher level information (object or scene level) for advanced tasks such as image understanding along with their applications to medical images. Advanced methods for fuzzy image processing and understanding are presented, including fuzzy spatial objects, geometry and topology, mathematical morphology, machine learning, verbal descriptions of image content, fusion, spatial relations, and structural representations. For each methodological aspect covered, illustrations from the medical imaging domain are provided. This is an ideal book for graduate students and researchers in the field of medical image processing.

This volume contains the proceedings of the 6th International Workshop on Soft Computing and Applications (WILF 2005), which took place in Crema, Italy, on September 15–17, 2005, continuing an established tradition of biannual meetings among researchers and developers from both academia and industry to report on the latest scienti?c and theoretical advances, to discuss and debate major issues, and to demonstrate state-of-the-art systems. This edition of the workshop included two special sessions, sort of subwo- shops, focusing on the application of soft computing techniques (or compu- tional intelligence) to image processing (SCIP) and bioinformatics (CIBB). WILF began life in Naples in 1995. Subsequent editions of this event took place in 1997 in Bari, in 1999 in Genoa, in 2001 in Milan, and in 2003 back in Naples. Soft computing, also known as computational intelligence, di?ers from c- ventional (hard) computing in that, unlike hard computing, it is tolerant of - precision, uncertainty, partial truth, and approximation. The guiding principle of soft computing is to exploit the tolerance for imprecision, uncertainty, partial truth, and approximation to achieve tractability, robustness, and low solution cost. The main components of soft computing are fuzzy logic, neural computing, and evolutionary computation.

This volume contains the proceedings of the 6th International Workshop on Soft Computing and Applications (WILF 2005), which took place in Crema, Italy, on September 15–17, 2005, continuing an established tradition of biannual meetings among researchers and developers from both academia and industry to report on the latest scienti?c and theoretical advances, to discuss and debate major issues, and to demonstrate state-of-the-art systems. This edition of the workshop included two special sessions, sort of subwo- shops, focusing on the application of soft computing techniques (or compu- tional intelligence) to image processing (SCIP) and bioinformatics (CIBB). WILF began life in Naples in 1995. Subsequent editions of this event took place in 1997 in Bari, in 1999 in Genoa, in 2001 in Milan, and in 2003 back in Naples. Soft computing, also known as computational intelligence, di?ers from c- ventional (hard) computing in that, unlike hard computing, it is tolerant of - precision, uncertainty, partial truth, and approximation. The guiding principle of soft computing is to exploit the tolerance for imprecision, uncertainty, partial truth, and approximation to achieve tractability, robustness, and low solution cost. The main components of soft computing are fuzzy logic, neural computing, and evolutionary computation.

Pattern recognition is a central topic in contemporary computer sciences, with continuously evolving topics, challenges, and methods, including machine learning, content-based image retrieval, and model- and knowledge-based - proaches, just to name a few. The Iberoamerican Congress on Pattern Recog- tion (CIARP) has become established as a high-quality conference, highlighting the recent evolution of the domain. These proceedings include all papers presented during the 15th edition of this conference, held in Sao Paulo, Brazil, in November 2010. As was the case for previous conferences, CIARP 2010 attracted parti- pants from around the world with the aim of promoting and disseminating - going research on mathematical methods and computing techniques for pattern recognition, computer vision, image analysis, and speech recognition, as well as their applications in such diverse areas as robotics, health, entertainment, space exploration, telecommunications, data mining, document analysis,and natural language processing and recognition, to name only a few of them. Moreover, it provided a forum for scienti?c research, experience exchange, sharing new kno- edge and increasing cooperation between research groups in pattern recognition and related areas. It is important to underline that these conferences have contributed sign- icantly to the growth of national associations for pattern recognition in the Iberoamerican region, all of them as members of the International Association for Pattern Recognition (IAPR).