Titlebook: Artificial Intelligence and Soft Computing; 17th International C Leszek Rutkowski,Rafał Scherer,Jacek M. Zurada Conference proceedings 2018

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https://doi.org/10.1007/978-3-642-85292-3 We present a strategy of complete segmentation of the proximal femur (right and left) in anterior-posterior pelvic radiographs using statistical models of shape and appearance for assistance in the diagnostics of diseases associated with femurs. Quantitative results are provided using the DICE coef

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paleolithic

,‘Vander Hulpen des Ghebrecs des Wiins’, with a variety of models, algorithms, structures, and applications. Smooth nonnegative matrix factorization assumes the estimated latent factors are locally smooth, and the smoothness is enforced by the underlying model or the algorithm. In this study, we extended one of the algorithms for this kin

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Grundrechnungsarten mit unbestimmten Zahlenon. Features selected from a set of 50 features were considered. Seven feature selection methods were used. The results of these selections were aggregated and found consistently positive for some of the features. Among them were primarily the features based on local adaptive thresholding and on Hil

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竖琴

Besondere Eigenschaften von Zahlenthm is based on establishing a low-dimensional space where the sampling (and optimization) is carried out via Particle Swarm Optimizer (PSO). The reduced space is found via Principal Component Analysis (PCA) performed for a set of previously found low-energy protein models. A high frequency term is

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https://doi.org/10.1007/978-3-663-13428-2 be effectively used to describe biometric features, in particular facial parts. In this paper, we present an original and innovative development of this approach augmented by a graphical interface that allows the user to get rid of restrictions in the form of certain numerical (linguistic) values,