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/10.1007/978-3-476-00813-8captured images is naturally imbalanced. We applied distribution of the training data set to estimate the actual distribution of the bird species in the test area. Species identification is based on the image classifier that is a hybrid of hierarchical and cascade models. The main idea is to train c

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Adversarial Examples in Deep Neural Networks: An Overview,behind the existence of adversarial examples as well as theories that consider the relation between the generalization error and adversarial robustness. Finally, various defenses against adversarial examples are also discussed.

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Representation Learning in Power Time Series Forecasting,resent data in such a way that it is suited for the task at hand. Once the neural network has learned such a representation of the data in a supervised or semi-supervised manner, it makes it possible to utilize this representation in the various available tasks for renewable energy. In our chapter,