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Titlebook: Computer Recognition Systems 2; Marek Kurzynski,Edward Puchala,Andrzej Zolnierek Conference proceedings 2007 Springer-Verlag Berlin Heidel

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书目名称Computer Recognition Systems 2
编辑Marek Kurzynski,Edward Puchala,Andrzej Zolnierek
视频video
概述Presents the latest results in computer recognition systems, pattern recognition, machine learning, web and data mining
丛书名称Advances in Intelligent and Soft Computing
图书封面Titlebook: Computer Recognition Systems 2;  Marek Kurzynski,Edward Puchala,Andrzej Zolnierek Conference proceedings 2007 Springer-Verlag Berlin Heidel
描述.Computer recognition systems are nowadays one of the most promising directions in artificial intelligence. This book presents actual comprehensive study of this field. It contains a collection of over one hundred carefully selected articles contributed by experts of pattern recognition. It reports on current research with respect to both methodology and applications. In particular, it includes the following sections:....Features, learning and classifiers,....Image processing and computer vision,....Speech and word recognition,....Medical applications,....Various applications....This book is a great reference tool for scientists who deal with the problems of designing computer pattern recognition systems. Its target readers can be the as well researchers as students of computer science, artificial intelligence or robotics..
出版日期Conference proceedings 2007
关键词Computational Intelligence; Computer Recognition Systems; Computer Vision; Data Mining; Signal; Web Minin
版次1
doihttps://doi.org/10.1007/978-3-540-75175-5
isbn_softcover978-3-540-75174-8
isbn_ebook978-3-540-75175-5Series ISSN 1867-5662 Series E-ISSN 1867-5670
issn_series 1867-5662
copyrightSpringer-Verlag Berlin Heidelberg 2007
The information of publication is updating

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E. Wetterer,R. D. Bauer,R. Busseieval problem. The original contribution of the presented work is related to the fusion of several shape and color descriptors and joining them into parallel or sequential structures giving considerable improvements in content-based image retrieval. The novelty is based on the fact that many existin
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Strategies of Shape and Color Fusions for Content Based Image Retrieval. It is clear that these representations have their own advantages and drawbacks. Our suggestion is to combine them to achieve better results in various areas, e.g. pattern recognition, object representation, image retrieval, by using optimal variants of particular descriptors (both, color and shape
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Trajectory Fusion for Multiple Camera Trackingroposed approach is based on the matching of multiple trajectories from multiple views using spatial and temporal information. These trajectories are represented as consecutive points of a joint ground plane in the world coordinate system that belong to the same tracked agent. We introduce an integr
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Multi-directional Multi-resolution Transforms for Zoom-Endoscopy Image Classificationx Wavelet Transform for the classification of zoom-endoscopy images. Further, we incorporate color channel information into the classification process and show, that this leads to superior classification results, compared to luminance-channel based image processing.
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Practical Evaluation of the Basic Concepts for Face Localizationactical value still needs to be verified. Moreover, while the techniques being described in publications are getting more and more sophisticated, they quite often rely on very straightforward concepts like edge maps. Therefore, the main goal of this work was not to propose another face localization
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