HIGHLIGHTS
- who: Siri S. Eide et al. from the Department of Computer Science, University of have published the Article: Deep Tower Networks for Efficient Temperature Forecasting from Multiple Data Sources, in the Journal: Sensors 2022, 22, 2802. of 19/02/2018
- what: To tackle this challenge the authors develop and investigate the usefulness of a novel learning method called tower networks. The authors compare the method to a number of meteorological baselines and simple statistical approaches. The authors compare the tower network with two core network architectures that are often used namely the convolutional neural network . . .
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