Download Artificial Intelligence and Soft Computing: 13th by Leszek Rutkowski, Marcin Korytkowski, Rafal Scherer, Ryszard PDF

By Leszek Rutkowski, Marcin Korytkowski, Rafal Scherer, Ryszard Tadeusiewicz, Lotfi A. Zadeh, Jacek M. Zurada

The two-volume set LNAI 8467 and LNAI 8468 constitutes the refereed lawsuits of the thirteenth overseas convention on synthetic Intelligence and tender Computing, ICAISC 2014, held in Zakopane, Poland in June 2014. The 139 revised complete papers provided within the volumes, have been rigorously reviewed and chosen from 331 submissions. The sixty nine papers incorporated within the first quantity are thinking about the subsequent topical sections: Neural Networks and Their purposes, Fuzzy structures and Their purposes, Evolutionary Algorithms and Their functions, type and Estimation, laptop imaginative and prescient, photo and Speech research and distinct consultation three: clever tools in Databases. The seventy one papers within the moment quantity are prepared within the following matters: information Mining, Bioinformatics, Biometrics and scientific purposes, Agent platforms, Robotics and keep watch over, man made Intelligence in Modeling and Simulation, quite a few difficulties of synthetic Intelligence, particular consultation 2: computer studying for visible info research and protection, specific consultation 1: purposes and houses of Fuzzy Reasoning and Calculus and Clustering.

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Additional resources for Artificial Intelligence and Soft Computing: 13th International Conference, ICAISC 2014, Zakopane, Poland, June 1-5, 2014, Proceedings, Part II

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CCIS, vol. 131, pp. 501–511. Springer, Heidelberg (2011) 8. : BRIEF: Binary robust independent elementary features. , Paragios, N. ) ECCV 2010, Part IV. LNCS, vol. 6314, pp. 778–792. Springer, Heidelberg (2010) 9. html 14 P. Artiemjew and P. G´ orecki 10. : Representations of keypoint-based semantic concept detection: A comprehensive study. IEEE Transactions on Multimedia 12(1), 42–53 (2010) 11. : A visual vocabulary for flower classification. In: Proc. of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol.

From mathematical point of view one can consider the set X as a collection of points in Rn (R denotes the set of real numbers). For intuition, each of the criterial values qi,j contributes to the overall quality of object i. Selection of some best 1 point (or points) is known as the Multiple Criteria Decision Making (MCDM), Multicriteria Optimization Problem (MOP), or Multicriteria Decision Making (MDM) [8,6]. Unfortunately, although such problems are often to be considered, there is no way to define a unique, best solution; what can be done is the definition of the non-dominated solutions (the so-called Pareto-optimal set) and some more or less subjective way of forming the final solution.

On Computer Vision and Pattern Recognition (2007) 15. : Information gain feature selection for ordinal text classification using probability re-distribution 16. : ORB: An efficient alternative to SIFT or SURF. In: International Conference on Computer Vision, Barcelona (2011) 17. : A study on mutual information-based feature selection for text categorization. Journal of Computational Information Systems 3(3), 1007–1012 (2007) 18. : Evaluating bag-of-visual-words representations in scene classification.

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