Applications and Innovations in Intelligent Systems XVI: by Tony Allen, Richard Ellis, Miltos Petridis PDF

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By Tony Allen, Richard Ellis, Miltos Petridis

ISBN-10: 1848822146

ISBN-13: 9781848822146

The papers during this quantity are the refereed program papers offered at AI-2008, the Twenty-eighth SGAI foreign convention on leading edge ideas and purposes of man-made Intelligence, held in Cambridge in December 2008. They current new and cutting edge functions of man-made intelligence throughout quite a lot of domain names; divided into sections on laptop studying, internet applied sciences, clever platforms and AI in healthiness Care. the amount additionally comprises the textual content of brief papers awarded as posters on the convention. this is often the 16th quantity within the program and ideas sequence, which bargains an annual photograph of the newest purposes of man-made intelligence throughout undefined, trade, schooling and govt. The Technical movement papers are released as a better half quantity less than the identify study and improvement in clever structures XXV.

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Extra info for Applications and Innovations in Intelligent Systems XVI: Proceedings of AI-2008, The Twenty-eighth SGAI International Conference on Innovative Techniques ... of Artificial Intelligence (v. 16)

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Principles of neurodynamics. Spartan books, New York (1962). 16. : Design and analysis of experiments. Wiley, Hoboken (2004). 47 Visualization of Agriculture Data Using Self-Organizing Maps Georg Ruß, Rudolf Kruse, Martin Schneider, Peter Wagner Abstract The importance of carrying out effective and sustainable agriculture is getting more and more obvious. In the past, additional fallow ground could be tilled to raise production. Nevertheless, even in industrialized countries agriculture can still improve on its overall yield.

Many time-frequency decomposition methods have been developed for analysis of non-stationary signals including sounds such as, for example, short-time Fourier transform (STFT) and continuous wavelet transform (CWT). Conversion of a time domain signal into timefrequency domain increases the size of feature space from a one-dimensional signal to a two-dimensional power spectrum such as a spectrogram in case of STFT or a scalogram in case of CWT. Typically, the feature space generated by time-frequency decomposition is reduced to a few significant coefficients by computing various empirically chosen statistics for time and frequency windows, thus making pattern recognition dependent on a small set of extracted features.

Neural Networks Vol. 17 pp. 1566-1579 (2006). 8. : Improved method of handwritten digit recognition tested on MNIST database. Image Vision Comput. Vol. 22 pp. 971-981 (2004). 9. : Flat image recognition in the process of microdevice assembly. Pattern Recogn. Lett. Vol. 25 pp. 107-118 (2004). 10. : Limited receptive area neural classifier for texture recognition of mechanically treated metal surfaces, Neurocomputing, Vol. 71 pp. 1413-1421 (2008). 11. : Neural network system for face recognition.

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Applications and Innovations in Intelligent Systems XVI: Proceedings of AI-2008, The Twenty-eighth SGAI International Conference on Innovative Techniques ... of Artificial Intelligence (v. 16) by Tony Allen, Richard Ellis, Miltos Petridis


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