Titlebook: Artificial Intelligence and Soft Computing — ICAISC 2004; 7th International Co Leszek Rutkowski,Jörg H. Siekmann,Lotfi A. Zadeh Conference

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The New Concept in Computer Vision: Automatic Understanding of the Imageson can be found as next step on the way starting from capturing of the images in digital form as two–dimensional data structures, next going throw images processing as a tool for enhancement of the images visibility and readability, applying images analysis algorithms for extracting selected feature

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Photodynamic Photorejuvenation,antage of this approach is that one requires only one CSVM which can admit multiple multivector inputs and it can carry multi-class classification. In contrast one would need many real valued SVMs for a multi-class problem which is time consuming.

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Facial Volumization with Fillerstential applications in many areas from engineering to psychology and neuroscience. The recent trends in BSS is to consider problems in the framework of probabilistic generative and tree structured graphical models and exploit a . knowledge about true nature and structure of latent (hidden) variable

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Facial-Oral Tract Therapy (F.O.T.T.)cusses how to visualize such multidimensional data, introducing a new projection on a lattice of hypercube nodes. It also discusses what type of information one may expect from visualization of the activity of hidden and output layers. Detailed analysis of the activity of RBF hidden nodes using this

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Facial-Oral Tract Therapy (F.O.T.T.)entations created by the hidden layers. Visualization of these representations leads to interesting conclusions about optimal architectures and training of such networks. The usefulness of visualization techniques is illustrated on parity problems solved with RBF networks.

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Chidozie Izuchukwu Princeton Dimlost values (a value was recorded but it is unavailable) and “do not care” conditions (the original values were irrelevant). Through the entire paper the same calculus, based on computations of blocks of attribute-value pairs, is used. Complete data are characterized by the indiscernibility relation