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Record Nr. |
UNISA996465989703316 |
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Titolo |
Advanced Intelligent Computing Theories and Applications [[electronic resource] ] : 7th International Conference, ICIC 2011, Zhengzhou, China, August 11-14, 2011. Revised Selected Papers / / edited by De-Shuang Huang, Yong Gan, Phalguni Gupta, M. Michael Gromiha |
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Pubbl/distr/stampa |
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Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2012 |
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ISBN |
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Edizione |
[1st ed. 2012.] |
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Descrizione fisica |
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1 online resource (XXIII, 729 p.) |
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Collana |
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Lecture Notes in Artificial Intelligence ; ; 6839 |
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Disciplina |
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Soggetti |
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Artificial intelligence |
Pattern recognition |
Application software |
Optical data processing |
Computers |
User interfaces (Computer systems) |
Artificial Intelligence |
Pattern Recognition |
Information Systems Applications (incl. Internet) |
Image Processing and Computer Vision |
Computation by Abstract Devices |
User Interfaces and Human Computer Interaction |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Bibliographic Level Mode of Issuance: Monograph |
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Nota di bibliografia |
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Includes bibliographical references and author index. |
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Sommario/riassunto |
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This book constitutes the thoroughly refereed post-conference proceedings of the 7th International Conference on Intelligent Computing, ICIC 2011, held in Zhengzhou, China, in August 2011. The 94 revised full papers presented were carefully reviewed and selected from 832 submissions. The papers are organized in topical sections on intelligent computing in scheduling; local feature descriptors for image processing and recognition; combinatorial and numerical optimization; |
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machine learning theory and methods; intelligent control and automation; knowledge representation/reasoning and expert systems; intelligent computing in pattern recognition; intelligent computing in image processing; intelligent computing in computer vision; biometrics with applications to individual security/forensic sciences; modeling, theory, and applications of positive systems; sparse manifold learning methods and applications; advances in intelligent information processing. |
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