Titlebook: New Advances in Intelligent Signal Processing; António E. Ruano,Annamária R. Várkonyi-Kóczy Book 20111st edition Springer-Verlag Berlin He

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Evolutionary Multiobjective Neural Network Models Identification: Evolving Task-Optimised Models,Their identification is often done iteratively in an . fashion focusing the first aspect. Frequently the selection of inputs, model structure, and model order are underlooked subjects by practitioners, because the number of possibilities is commonly huge, thus leaving the designer at the hands of th

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Structural Learning Model of the Neural Network and Its Application to LEDs Signal Retrofit,ined in terms of mixed integer quadratic programming. Simulation results show that computation time is up to one fifth faster than conventional BMs. The computational efficiency of the resulting double-layer BM is approximately expressed as the ratio . divided by ., where n denotes the number of sel

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Adjourn

Design of Fuzzy Relation-Based Image Sharpeners, be adopted in the design of a complete image enhancement systems and successfully address conflicting tasks such as detail sharpening and noise cancellation. For this purpose, the different behaviors of fuzzy relation-based high-pass filters and noise smoothers are explained along with the effects

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Application of Fuzzy Logic and Lukasiewicz Operators for Image Contrast Control, There is a wide variety of contrast control techniques. However, most are not suitable for hardware implementation. A technique to control the contrast in images based on the application of Lukasiewicz algebra operators and fuzzy logic is described. In particular, the technique is based on the boun

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Low Complexity Situational Models in Image Quality Improvement, extraction, high dynamic range (HDR) imaging methods based on soft computing models have been shown to be very effective in removing noise without destroying the useful information contained in the image data. Although, to distinguish among noise and useful information is not an easy task and may h

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Weakly Supervised Learning: Application to Fish School Recognition,rmation of the training dataset is provided as a prior knowledge for each class. This prior knowledge is coming from a global proportion annotation of images. In this chapter, we compare three opposed classification models in a weakly supervised classification issue: a generative model, a discrimina

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