Titlebook: Deep Learning: Algorithms and Applications; Witold Pedrycz,Shyi-Ming Chen Book 2020 Springer Nature Switzerland AG 2020 Computational Inte

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https://doi.org/10.1007/978-3-030-31760-7Computational Intelligence; Machine Learning; Computer Vision; Natural Language Processing; Deep Learnin

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978-3-030-31762-1Springer Nature Switzerland AG 2020

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Deutsche Klassiker im Nationalsozialismuswork learn will only be able to learn a linear relation between input and the desired output. The chapter introduces the reader to why activation functions are useful and their immense importance in making deep learning successful. A detailed survey of several existing activation functions?is provid

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Abstand, nicht Widerstand: Max Kommerelltribute up?to . to the energy mix. However, the challenges that arise with the integration of those variable energy resources are various. Some of these tasks are short-term and long-term power generation forecasts, load?forecasts, integration of multiple numerical weather prediction (NWP) models, s

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Literatur in der Weimarer Republik, making this possible because it can leverage the huge amount of training data that comes from autonomous car sensors. Automatic recognition of traffic light and vehicle signal is a perception module critical to autonomous vehicles because a deadly car accident could happen if a vehicle fails to fol

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https://doi.org/10.1007/978-3-476-04953-7as are utilised to access underwater environments. Up till now image data has been processed by human observers which is costly and often represents repetitive mundane work. Deep learning techniques that can automatically classify objects can increase the speed and the amounts of data that can be pr