Download Artificial Intelligence Perspectives and Applications: by Radek Silhavy, Roman Senkerik, Zuzana Kominkova Oplatkova, PDF

By Radek Silhavy, Roman Senkerik, Zuzana Kominkova Oplatkova, Zdenka Prokopova, Petr Silhavy

This quantity relies at the learn papers provided within the 4th machine technological know-how online Conference.

The quantity man made Intelligence views and purposes provides new methods and strategies to real-world difficulties, and specifically, exploratory study that describes novel techniques within the box of man-made intelligence. specific emphasis is laid on smooth tendencies in chosen fields of curiosity. New algorithms or equipment in quite a few fields also are presented.

The laptop technology online convention (CSOC 2015) is meant to supply a world discussion board for discussions at the most modern high quality study leads to all components relating to machine Science.

The addressed subject matters are the theoretical elements and functions of desktop technological know-how, man made Intelligences, Cybernetics, Automation keep watch over idea and software program Engineering.

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Extra resources for Artificial Intelligence Perspectives and Applications: Proceedings of the 4th Computer Science On-line Conference 2015 (CSOC2015), Vol 1: Artificial Intelligence Perspectives and Applications

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Image Ground truth people, meadow, fence, tree, sky girl, skirt, house, waistcoat, hill PLSAWORDS grass, tree, sky, stone, building sky, sand, wall, desert, landscape girl, sky, people, cloud, hill [22] HGDM tree, sky, meadow, people, house people, meadow, lawn, tree, sky AIAFS girl, skirt, house, land, hill waterfall, forest, tourist, river, ravine water, forest, tree, grass, cloud tree, cloud, house, sky, river waterfall, forest, snow, river, ravine lawn, garden, tree, cloud, sky waterfall, forest, mountain, river, ravine lawn, tree, cloud, grassland, sky lawn, path, tree, cloud, sky Fig.

Com/science/article/pii/S1077314210002511 19. : Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(7), 971–987 (2002) 20. : A comparative study of texture measures with classification based on featured distributions. com/science/article/pii/ 0031320395000674 21. : The feret evaluation methodology for face-recognition algorithms. IEEE Transactions on Pattern Analysis and Machine Intelligence 22(10), 1090–1104 (2000) 22.

The mutual information (MI) is used to measure contribution of each image feature. We introduce a nonlinear factor to evaluation function of the feature selection approach to measure its performance. The experiment results show that proposed AIA approach achieves higher performance than the existing most AIA approaches, its performance is satisfactory. Keywords: Automatic image annotation, Feature selection, Mutual information, Performance. 1 Introduction With exponential growth of digital images on online image sites, automatic image annotation (AIA) now become an important issue of image management and image analysis.

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