By Ted Scully, Kenneth N. Brown (auth.), Tony Allen BA, MSc, PhD, Richard Ellis BSc, MSc, Miltos Petridis DipEng, MBA, PhD, MBCS, AMBA (eds.)

ISBN-10: 1848822146

ISBN-13: 9781848822146

ISBN-10: 1848822154

ISBN-13: 9781848822153

The papers during this quantity are the refereed program papers offered at AI-2008, the Twenty-eighth SGAI foreign convention on leading edge concepts and functions of synthetic Intelligence, held in Cambridge in December 2008.

They current new and cutting edge purposes of man-made intelligence throughout quite a lot of domain names; divided into sections on desktop studying, internet applied sciences, clever structures and AI in overall healthiness Care. the quantity additionally contains the textual content of brief papers provided as posters on the conference.

This is the 16th quantity within the program and options sequence, which bargains an annual picture of the most recent functions of synthetic intelligence throughout undefined, trade, schooling and executive.

The Technical circulate papers are released as a spouse quantity less than the identify learn and improvement in clever platforms 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 and Applications of Artificial Intelligence

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31283131 (2007). 14. : The illustrated wavelet transform handbook. Institute of Physics Publishing, Bristol (2002). 15. : 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.

4 Discussion Obtained results suggest high efficiency and reliability of the proposed method, though tests on a larger database would be needed for a conclusive proof. An important advantage of the proposed method is utilization of a double-redundant approach to identification of significant features. First, time-frequency decomposition method provides a redundant description of a sound instance, therefore increasing chances for random selection of a significant feature. Second, randomly assigned redundant connections between the sensor and associative layers ensure multiplicity of extracted random features.

The neuron with the largest excitation (winner neuron) represents the recognized class. 3 Results The proposed methodology was tested on two datasets composed correspondingly of spectrograms and scalograms of sound instances. Each database contained eighty 256x256 pixels grayscale images (20 for each of 4 classes). e. the validation set for each class was chosen randomly from the database and the rest of the database was used for training. In each experiment we performed 50 runs of the holdout cross-validation to obtain statistically reliable results.

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Applications and Innovations in Intelligent Systems XVI: Proceedings of AI-2008, the Twenty-eighth SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence by Ted Scully, Kenneth N. Brown (auth.), Tony Allen BA, MSc, PhD, Richard Ellis BSc, MSc, Miltos Petridis DipEng, MBA, PhD, MBCS, AMBA (eds.)


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