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Titlebook: Artificial Intelligence and Soft Computing; 19th International C Leszek Rutkowski,Rafa? Scherer,Jacek M. Zurada Conference proceedings 2020

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發(fā)表于 2025-3-23 12:33:09 | 只看該作者
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Monoranjan Maiti,Samir Maity,Arindam RoyBoth classes of algorithms have their history, principles and represent two different biological areas, converted to computer technology. Despite fact that scientists already exhibited that both systems exhibit almost the same behavior dynamics (chaotic regimes etc.), researchers still take both cla
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發(fā)表于 2025-3-24 05:08:22 | 只看該作者
Facets of Uncertainties and Applicationstongue. Currently, deep neural networks are the most successful technology for this task. The efficient solution requires methods that do not simply process single images, but are able to extract the tongue movement information from a sequence of video frames. One option for this is to apply recurre
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發(fā)表于 2025-3-24 09:29:00 | 只看該作者
Facets of Uncertainties and Applicationss. The order flow is the microsecond stream of orders arriving at the exchange, driving the formation of prices seen on the price chart of a stock or currency. To test the stationarity of our proposed model we train our model on data before the 2017 Bitcoin bubble period and test our model during an
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Facets of Uncertainties and Applicationsned two neural networks to achieve reliable 6D object pose estimation on such images. The first neural network detects fiducial points of objects, which are then fed to a PnP algorithm responsible for pose estimation. The second one is an rotation regression network delivering at the output the quat
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https://doi.org/10.1007/978-81-322-2301-6raphical representations: chromograms and spectrograms. We have used a large dataset of music divided into eight genres, with certain overlapping musical features. Key, style-defining elements and the overall character of specific genres are represented in our proposed visual representation and reco
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https://doi.org/10.1007/978-3-030-61401-0artificial intelligence; classification; computer networks; computer vision; correlation analysis; evolut
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