Titlebook: Artificial Neural Networks - ICANN 2006; 16th International C Stefanos Kollias,Andreas Stafylopatis,Erkki Oja Conference proceedings 2006 S

大约冬季

Untersuchungen an Cowper und Cowpersteinen,ls. Pixel regions with consistent color and motion properties are extracted from these 3D volumes by a space-time segmentation technique based on a novel machine learning algorithm. Each region is then described by a high-dimensional point whose components represent the average position, motion velo

Cloudburst

Friedrich Harders,Sigismund Kienow expanding the user’s query with semantically related concepts, enhancing in parallel the quality of retrieval to a large extend. Query analyzers broaden the user’s information needs from classical term-based to conceptually representations, using knowledge from relevant ontologies and theirs’ prope

FOIL

https://doi.org/10.1007/978-3-662-11741-5 retrieval. In the coin retrieval application dealt in this paper, the goal is to retrieve images of coins that are similar to a query coin based on features extracted from color or grayscale images. To assure improved performance at various scales, orientations or in the presence of noise, a set of

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Encephalitis

Lagerung von Steinkohlen Oberschlesiens,treat their results as multivariate variable with the latent components having constructive or destructive impact on prediction results. The filtration of those destructive components and proper mixing of those constructive should improve final prediction results. The filtration process can be perfo

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Monographien zur Feuerungstechnik involving time series forecasting use the Sigma-Point Kalman Filters, however they do not use an ensemble of them, which could achieve a better performance. The REC analysis is a powerful technique for visualization and comparison of regression models. The objective of this work is to advocate the

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coagulate

Temperatur- und Zugmessungen am Schornstein, it may be hard to achieve good prediction results. In this paper, we investigate Gaussian linear regression filters for parameter estimation in state-space models and we propose new long-term prediction strategies. Experiments using the EM-algorithm for training of nonlinear state-space models show