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

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Deep Learning Case Study on Imbalanced Training Data for Automatic Bird Identification,ons. However, it is improbable that a single deterrent method would work for all bird species in a given area. An automatic bird identification system is needed in order to develop bird species level deterrent methods. This system is the first and necessary part of the entirety that is eventually ab

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Deep Learning for Building Occupancy Estimation Using Environmental Sensors,ncy, which directly affects energy-related control systems in buildings. Among varieties of sensors for occupancy estimation, environmental sensors have unique properties of non-intrusion and low-cost. In general, occupancy estimation using environmental sensors contains feature engineering and lear

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Abstand, nicht Widerstand: Max Kommerellresent 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,

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Die Deutsche Literatur des Exils,structed within seconds, namely, orders of magnitude faster than existing solutions. Reconstructed models are free of human biases since no initial model or numerical technique tuning is required. This chapter is a significant extension of previous published material and provides a detailed explanat

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