Titlebook: Highly Redundant Sensing in Robotic Systems; Julius T. Tou,Jens G. Balchen Conference proceedings 1990 Springer-Verlag Berlin Heidelberg 1

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V. Cantoni,M. Ferretti,M. Saviniselection on the output of one or more search engines using the preferences that it has learned. We also introduce a “relevance metric” to compare the performance of our Intelligent Internet Search Assistant against a few search engines, showing that it provides better performance.

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he rule of thumb..In this paper we get advantage of Web Image Context Extraction (WICE) using visual web-page parsing and specific distance metrics and following this we locate key terms within this text to index the image using language models. In this way, the proposed method is totally learning f

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A. Meystelhe rule of thumb..In this paper we get advantage of Web Image Context Extraction (WICE) using visual web-page parsing and specific distance metrics and following this we locate key terms within this text to index the image using language models. In this way, the proposed method is totally learning f

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Gerardo Beni,Jing Wang is to present preliminary work on a semantic modeling and simulation approach that aims to facilitate commanders of military/search-and-rescue operations to effectively support critical and life-saving decision-making, while handling interoperability and cybersecurity issues on the Internet of Unde

Biofeedback

Jens G. Balchen,Fredrik Dessenross-channel fraud detection method on a real banking dataset which is highly imbalanced in terms of frauds which is another challenge in the fraud detection problem. We use our trained model to score real-time cross-channel transactions by a leading private bank in Turkey. As a result, our approach

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Highly Redundant Sensing in Robotic Systems978-3-642-84051-7Series ISSN 0258-1248

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Structural Solution of Highly Redundant Sensing in Robotic SystemsReasons for and problems concerning the integration of large number of sensors in robotic systems are discussed. This includes data collection, coordination and integration by means of state estimation. The need for unified approaches in handling highly redundant sensory systems is stated and solutions suggested.

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https://doi.org/10.1007/978-3-642-84051-7Motor; Sensor; cognition; control; knowledge; knowledge-based system; knowledge-based systems; learning; mea