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Download PDF by Abdelhamid Bouchachia (eds.): Adaptive and Intelligent Systems: Third International

By Abdelhamid Bouchachia (eds.)

ISBN-10: 331911297X

ISBN-13: 9783319112978

ISBN-10: 3319112988

ISBN-13: 9783319112985

This publication constitutes the complaints of the foreign convention on Adaptive and clever platforms, ICAIS 2014, held in Bournemouth, united kingdom, in September 2014. the nineteen complete papers incorporated in those court cases including the abstracts of four invited talks, have been conscientiously reviewed and chosen from 32 submissions. The contributions are prepared lower than the subsequent topical sections: advances in characteristic choice; clustering and type; adaptive optimization; advances in time sequence analysis.

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Extra resources for Adaptive and Intelligent Systems: Third International Conference, ICAIS 2014, Bournemouth, UK, September 8-10, 2014. Proceedings

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Therefore the EM algorithm consists of getting the mixture parameters that maximize the log-likelihood function given by M N Zij log p(Xi |ξj )pj L(Θ, Z, X ) = (4) j=1 i=1 However, before applying the EM algorithm, we need to choose some initial values for the mixture parameters. In our case, we use the K-means algorithm to choose the initial values. Then, we employ the EM iterative algorithm which produces a sequence of estimates to the mixture parameters Θ(t) , for t = 0, . , until a certain convergence criterion is satisfied through two different steps: the expectation and maximization.

SURF: Speeded up robust features. , Pinz, A. ) ECCV 2006, Part I. LNCS, vol. 3951, pp. 404–417. Springer, Heidelberg (2006) 6. : Video google: A text retrieval approach to object matching in videos. In: IEEE International Conference on Computer Vision (ICCV), pp. 1470–1477 (2003) A Novel Method for Scene Categorization 39 7.

1. Sample images from the SUN dataset; First Row: (a) Abbey, (b) Airplane cabin, (c) Airport terminal, (d) Alley, (e) Amusement arcade, (f) Amusement park, (g) Apartment building, (h) Apse; Second Row: (a) Aquarium, (b) Cabin, (c) Candy store, (d) Office, (e) Oilrig, (f) Parking Garage, (g) Raft, (h) Village 4 Conclusion In this study, an improved visual vocabulary approach is implemented for extracting important keypoints in scenes. Our method proposes to use a soft assignment and thus considers the uncertainty present in the image descriptor level.

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Adaptive and Intelligent Systems: Third International Conference, ICAIS 2014, Bournemouth, UK, September 8-10, 2014. Proceedings by Abdelhamid Bouchachia (eds.)


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