Advances in Quantitative Analysis of Finance and Accounting is an annual publication designed to disseminate developments in the quantitative analysis of finance and accounting. The publication is a forum for statistical and quantitative analyses of issues in finance and accounting, as well as applications of quantitative methods to problems in...
Master cutting-edge Level 2 fusion techniques that help you develop powerful situation assessment services with eye-popping capabilities and performance with this trail-blazing resource. The book explores object and situation fusion processes with an appropriate handling of uncertainties, and applies cutting-edge artificial intelligence and...
Computational techniques based on simulation have now become an essential part of the statistician's toolbox. It is thus crucial to provide statisticians with a practical understanding of those methods, and there is no better way to develop intuition and skills for simulation than to use simulation to solve statistical problems. Introducing...
This textbook provides a comprehensive introduction to the theories, techniques and applications of image fusion. It is aimed at advanced undergraduate and first-year graduate students in electrical engineering and computer science. It should also be useful to practicing engineers who wish to learn the concepts of image fusion and use them in...
New sequencing technologies have broken many experimental barriers to genome scale sequencing, leading to the extraction of huge quantities of sequence data. This expansion of biological databases established the need for new ways to harness and apply the astounding amount of available genomic information and convert it into substantive...
Bayesian networks have received a lot of attention over the last few decades from both scientists and engineers, and across a number of fields, including artificial intelligence (AI), statistics, cognitive science, and philosophy.
Perhaps the largest impact that Bayesian networks have had is on the field of AI, where they were...
Techniques of vision-based motion analysis aim to detect, track, identify, and generally understand the behavior of objects in image sequences. With the growth of video data in a wide range of applications from visual surveillance to human-machine interfaces, the ability to automatically analyze and understand object motions from video...
This book describes the optimization methods most commonly encountered in signal and image processing: artificial evolution and Parisian approach; wavelets and fractals; information criteria; training and quadratic programming; Bayesian formalism; probabilistic modeling; Markovian approach; hidden Markov models; and metaheuristics (genetic...
Updated and expanded, Bayesian Artificial Intelligence, Second Edition provides a practical and accessible introduction to the main concepts, foundation, and applications of Bayesian networks. It focuses on both the causal discovery of networks and Bayesian inference procedures. Adopting a causal interpretation of Bayesian...
We have been very pleased, beyond our expectations, with the reception of
the first edition of this book. Bioinformatics, however, continues to evolve
very rapidly, hence the need for a new edition. In the past three years, fullgenome
sequencing has blossomed with the completion of the sequence of
the fly and the first draft of the...
Over the last few decades, energy minimization methods have become an established
paradigm to resolve a variety of challenges in the fields of computer vision
and pattern recognition. While traditional approaches to computer vision were
often based on a heuristic sequence of processing steps and merely allowed a
very limited...
This volume contains the papers presented at the 14th International Workshop
on Approximation Algorithms for Combinatorial Optimization Problems
(APPROX 2011) and the 15th International Workshop on Randomization and
Computation (RANDOM 2011), which took place concurrently in Princeton
University, USA, during August 17–19,...
