Applied Pattern Recognition [electronic resource] /edited by Horst Bunke, Abraham Kandel, Mark Last.
by Bunke, Horst [editor.]; Kandel, Abraham [editor.]; Last, Mark [editor.]; SpringerLink (Online service).
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BookSeries: Studies in Computational Intelligence: 91Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2008.Description: online resource.ISBN: 9783540768319.Subject(s): Engineering | Artificial intelligence | Computer vision | Optical pattern recognition | Mathematics | Engineering mathematics | Engineering | Appl.Mathematics/Computational Methods of Engineering | Pattern Recognition | Artificial Intelligence (incl. Robotics) | Computer Imaging, Vision, Pattern Recognition and Graphics | Applications of MathematicsDDC classification: 519 Online resources: Click here to access online | Item type | Current location | Call number | Status | Date due | Barcode |
|---|---|---|---|---|---|
| TA640-643 (Browse shelf) | Available | ||||
| Long Loan | MAIN LIBRARY | TA329-348 (Browse shelf) | Available |
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| Life in the Universe | TA329-348 Computational Intelligence in Multimedia Processing: Recent Advances | TA329-348 Intelligent Decision Making: An AI-Based Approach | TA329-348 Applied Pattern Recognition | RC841-858.P35 Hepatology Textbook and Atlas | HB1-846.8 Evolution of Non-Expected Utility Preferences | TA177.4-185 Dynamics in Logistics |
Face Recognition Applications -- Skin-based Face Detection-Extraction and Recognition of Facial Expressions -- Facial Image Processing -- Face Recognition and Pose Estimation with Parametric Linear Subspaces -- Spatio-Temporal Patterns -- 4D Segmentation of Cardiac Data Using Active Surfaces with Spatiotemporal Shape Priors -- Measuring Similarity Between Trajectories of Mobile Objects -- Graph-Based Methods -- Matching of Hypergraphs — Algorithms, Applications, and Experiments -- Feature-Driven Emergence of Model Graphs for Object Recognition and Categorization -- Special Applications -- A Wavelet-based Statistical Method for Chinese Writer Identification -- Texture Analysis by Accurate Identification of a Generic Markov–Gibbs Model.
A sharp increase in the computing power of modern computers, accompanied by a decrease in the data storage costs, has triggered the development of extremely powerful algorithms that can analyze complex patterns in large amounts of data within a very short period of time. Consequently, it has become possible to apply pattern recognition techniques to new tasks characterized by tight real-time requirements (e.g., person identification) and/or high complexity of raw data (e.g., clustering trajectories of mobile objects). The main goal of this book is to cover some of the latest application domains of pattern recognition while presenting novel techniques that have been developed or customized in those domains.
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