Terry Caelli – författare

In this groundbreaking new volume, computer researchers discuss the development of technologies and specific systems that can interpret data with respect to domain knowledge. Although the chapters each illuminate different aspects of image interpretation, all utilize a common approach - one that asserts such interpretation must involve perceptual learning in terms of automated knowledge acquisition and application, as well as feedback and consistency checks between encoding, feature extraction, and the known knowledge structures in a given application domain. The text is profusely illustrated with numerous figures and tables to reinforce the concepts discussed.

The aim of this book, originally published in 1984, was to bring together a number of approaches to this important topic. Significant advances had been made in the two decades before publication in our understanding of many aspects of the coding that occurs along the visual pathways. The major developments had been associated with probing the nature of "logical" processes, whether physiologically or psychophysically, and relatively less attention had been devoted to the problem of how such locally coded knowledge is put together to yield coherent representations of spatially (and temporally) extended patterns – that is, to figural synthesis. Thus, while a great deal was known about the responses of individual cells in the visual system to controlled stimulation, and about the specificity of the orientational and spatial-frequency tuning of channels assessed psychophysically, there had been much less discussion of how such knowledge could be brought to bear on the general problems of understanding pattern recognition.

The aim of this book, originally published in 1984, was to bring together a number of approaches to this important topic. Significant advances had been made in the two decades before publication in our understanding of many aspects of the coding that occurs along the visual pathways. The major developments had been associated with probing the nature of "logical" processes, whether physiologically or psychophysically, and relatively less attention had been devoted to the problem of how such locally coded knowledge is put together to yield coherent representations of spatially (and temporally) extended patterns – that is, to figural synthesis. Thus, while a great deal was known about the responses of individual cells in the visual system to controlled stimulation, and about the specificity of the orientational and spatial-frequency tuning of channels assessed psychophysically, there had been much less discussion of how such knowledge could be brought to bear on the general problems of understanding pattern recognition.

In this groundbreaking new volume, computer researchers discuss the development of technologies and specific systems that can interpret data with respect to domain knowledge. Although the chapters each illuminate different aspects of image interpretation, all utilize a common approach - one that asserts such interpretation must involve perceptual learning in terms of automated knowledge acquisition and application, as well as feedback and consistency checks between encoding, feature extraction, and the known knowledge structures in a given application domain. The text is profusely illustrated with numerous figures and tables to reinforce the concepts discussed.

Machine learning is a relatively new branch of artificial intelligence. The field has undergone a significant period of growth in the 1990s, with many new areas of research and development being explored. In this text, the authors take a broad brush view of the field in an attempt to bring together many of the results that have been achieved, presenting a general taxonomy of the field and the various key representative algorithms.

This volume contains all papers presented at SSPR 2004 and SPR 2004, hosted by the Instituto de Telecomunicac" ,oes/Instituto Superior T' ecnico, Lisbon, Portugal, August 18-20, 2004. This was the fourth time that the two workshops were held back-to-back. The SSPR was the tenth International Workshop on Structural and Synt- tic Pattern Recognition, and the SPR was the ?fth International Workshop on Statistical Techniques in Pattern Recognition. These workshops have traditi- ally been held in conjunction with ICPR (International Conference on Pattern Recognition), and are the major events for technical committees TC2 and TC1, respectively, of the International Association for Pattern Recognition (IAPR). The workshops were closely coordinated, being held in parallel, with plenary talks and a common session on hybrid systems. This was an attempt to resolve thedilemmaofhowto dealwiththeneedfornarrow-focusspecializedworkshops yet accommodate the presentation of new theories and techniques that blur the distinction between the statistical and the structural approaches.A total of 219 papers were received from many countries, with the subm- sion and reviewing processes being carried out separately for each workshop. A total of 59 papers were accepted for oral presentation and 64 for posters. In - dition, four invited speakers presented informative talks and overviews of their research. They were: Alberto Sanfeliu, from the Technical University of Cata- nia, Spain; Marco Gori, from the University of Siena, Italy; Nello Cristianini, from the University of California, USA; and Erkki Oja, from Helsinki University of Technology, Finland, winner of the 2004 Pierre Devijver Award.