Image Analysis and Recognition: 13th International by Aurélio Campilho, Fakhri Karray

By Aurélio Campilho, Fakhri Karray

This ebook constitutes the completely refereed complaints of the thirteenth foreign convention on snapshot research and popularity, ICIAR 2016, held in Póvoa de Varzim, Portugal, in July 2016.
The seventy nine revised complete papers and 10 brief papers awarded have been rigorously reviewed and chosen from 167 submissions. The papers are geared up within the following topical sections: Advances in info Analytics and development popularity with functions, photo Enhancement and recovery, picture caliber review, picture Segmentation, trend research and popularity, function Extraction, Detection and popularity, Matching, movement and monitoring, 3D computing device imaginative and prescient, RGB-D digital camera purposes, visible notion in Robotics, Biometrics, Biomedical Imaging, mind Imaging, Cardiovascular snapshot research, picture research in Ophthalmology, rfile research, purposes, and Obituaries.

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135–158. Springer, Berlin (2007) 20. : Self-Organizing Maps, 3rd edn. Springer, Berlin (2001) 21. : Self-organizing time map: an abstraction of temporal multivariate patterns. Neurocomputing 99, 496–508 (2013) 22. : Analysis and Study of Incremental K-Means Clustering Algorithm. , Kumar, S. ) HPAGC 2011. CCIS, vol. 169, pp. 338–341. Springer, Heidelberg (2011) 23. : Incremental kernel spectral clustering for online learning of non-stationary data. Neurocomputing 139, 246–260 (2014) 24. : Incremental spectral clustering and its application to topological mapping.

In: Robotics and Automation, ICRA, pp. 1856–1861 (2008) 26. : Density-based clustering over an evolving data stream with noise. In: Proceedings of the Sixth SIAM International Conference on Data Mining (SDM), pp. 328–339 (2006) 27. : Catching the trend: a framework for clustering concept-drifting categorical data. IEEE Trans. Knowl. Data Eng. 21(5), 652–665 (2009) 28. : Trend analysis of categorical data streams with a concept change method. Inform. Sci. 276, 160–173 (2007) 29. : A web usage mining framework for mining evolving user profiles in dynamic web sites.

With model compression (4) the computational demands of the feature extraction could be significantly reduced with just a minor loss in accuracy. 6M images; model compression can be successfully applied also to compress state-of-the-art face verification algorithms [14]. Our results together with these two papers strengthen our hypothesis that fine-tuning combined with model compression makes it possible to achieve accuracy competitive to state-of-the-art in face verification using an efficient, compact model and less data.

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