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Computer Vision - ECCV 2004
Welcome to the proceedings of the 8th European Conference on Computer - sion! Following a very successful ECCV 2002, the response to our call for papers was almost equally strong – 555 papers were submitted. We accepted 41 papers for oral and 149 papers for poster presentation. Several innovations were introduced into the review process. First, the n- ber of program committee members was increased to reduce their review load. We managed to assign to program committee members no more than 12 papers. Second, we adopted a paper ranking system. Program committee members were asked to rank all the papers assigned to them, even those that were reviewed by additional reviewers. Third, we allowed ...
Invariant Recognition of Visual Objects
This Research Topic will focus on how the visual system recognizes objects regardless of variations in the viewpoint, illumination, retinal size, background, etc. Contributors are encouraged to submit articles describing novel results, models, viewpoints, perspectives and/or methodological innovations relevant to this topic. The issues we wish to cover include, but are not limited to, perceptual invariance under one or more of the following types of image variation: • Object shape • Task • Viewpoint (from the translation and rotation of the object relative to the viewer) • Illumination, shading, and shadows • Degree of occlusion • Retinal size • Color • Surface texture • Vi...
Machine Learning and Knowledge Discovery in Databases
The three volume set LNAI 9284, 9285, and 9286 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2015, held in Porto, Portugal, in September 2015. The 131 papers presented in these proceedings were carefully reviewed and selected from a total of 483 submissions. These include 89 research papers, 11 industrial papers, 14 nectar papers, 17 demo papers. They were organized in topical sections named: classification, regression and supervised learning; clustering and unsupervised learning; data preprocessing; data streams and online learning; deep learning; distance and metric learning; large scale learning and big data; matrix and tensor analysis; pattern and sequence mining; preference learning and label ranking; probabilistic, statistical, and graphical approaches; rich data; and social and graphs. Part III is structured in industrial track, nectar track, and demo track.
Multiscale and Multiresolution Methods
Many computionally challenging problems omnipresent in science and engineering exhibit multiscale phenomena so that the task of computing or even representing all scales of action is computationally very expensive unless the multiscale nature of these problems is exploited in a fundamental way. Some diverse examples of practical interest include the computation of fluid turbulence, structural analysis of composite materials, terabyte data mining, image processing, and a multitude of others. This book consists of both invited and contributed articles which address many facets of efficient multiscale representation and scientific computation from varied viewpoints such as hierarchical data representations, multilevel algorithms, algebraic homogeni- zation, and others. This book should be of particular interest to readers interested in recent and emerging trends in multiscale and multiresolution computation with application to a wide range of practical problems.
Come, Let’s Play
This book does not tell a story. Instead, it is about stories. Or rather, in technical terms, it is about scenarios. Scenarios of system behavior. It con centrates on reactive systems, be they software or hardware, or combined computer-embedded systems, including distributed and real-time systems. We propose a different way to program such systems, centered on inter object scenario-based behavior. The book describes a language, two tech niques, and a supporting tool. The language is a rather broad extension of live sequence charts (LSCs), the original version of which was proposed in 1998 by W. Damm and the first-listed author of this book. The first of the two techniques, called play-in, is...
Algorithms in Algebraic Geometry
In the last decade, there has been a burgeoning of activity in the design and implementation of algorithms for algebraic geometric computation. The workshop on Algorithms in Algebraic Geometry that was held in the framework of the IMA Annual Program Year in Applications of Algebraic Geometry by the Institute for Mathematics and Its Applications on September 2006 is one tangible indication of the interest. This volume of articles captures some of the spirit of the IMA workshop.
Predicting movie ratings and recommender systems
A 195-page monograph by a top-1% Netflix Prize contestant. Learn about the famous machine learning competition. Improve your machine learning skills. Learn how to build recommender systems. What's inside:introduction to predictive modeling,a comprehensive summary of the Netflix Prize, the most known machine learning competition, with a $1M prize,detailed description of a top-50 Netflix Prize solution predicting movie ratings,summary of the most important methods published - RMSE's from different papers listed and grouped in one place,detailed analysis of matrix factorizations / regularized SVD,how to interpret the factorization results - new, most informative movie genres,how to adapt the algorithms developed for the Netflix Prize to calculate good quality personalized recommendations,dealing with the cold-start: simple content-based augmentation,description of two rating-based recommender systems,commentary on everything: novel and unique insights, know-how from over 9 years of practicing and analysing predictive modeling.
Vision and Brain
An interdisciplinary book that surveys experimental and theoretical discoveries concerning how a brain sees and how insights about biological vision can be used to develop more effective algorithms for image processing in technology.
Machine Learning and Knowledge Discovery in Databases
The three volume set LNAI 9284, 9285, and 9286 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2015, held in Porto, Portugal, in September 2015. The 131 papers presented in these proceedings were carefully reviewed and selected from a total of 483 submissions. These include 89 research papers, 11 industrial papers, 14 nectar papers, 17 demo papers. They were organized in topical sections named: classification, regression and supervised learning; clustering and unsupervised learning; data preprocessing; data streams and online learning; deep learning; distance and metric learning; large scale learning and big data; matrix and tensor analysis; pattern and sequence mining; preference learning and label ranking; probabilistic, statistical, and graphical approaches; rich data; and social and graphs. Part III is structured in industrial track, nectar track, and demo track.
Learning OpenCV
"This library is useful for practitioners, and is an excellent tool for those entering the field: it is a set of computer vision algorithms that work as advertised."-William T. Freeman, Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology Learning OpenCV puts you in the middle of the rapidly expanding field of computer vision. Written by the creators of the free open source OpenCV library, this book introduces you to computer vision and demonstrates how you can quickly build applications that enable computers to "see" and make decisions based on that data. Computer vision is everywhere-in security systems, manufacturing inspection systems, medical im...
