Artificial Intelligence and Energy

Features learned by a convo- lutional neural network (CNN), bottleneck features from existing models and manually extracted features from the spectrograms comprised the three

A Bird’s Eye View on Requirements Engineering and Machine learning, the 25th Asia-Pacific Software Engineering Conference 2018 (APSEC 2018), December 4-7, Nara, Japan.. Feldt

Any set of models created by machine learning algorithms represents information inherited in the underlying training data and can therefore be considered a knowledge base.. In

And this is where machine learning can be useful, offering a series of techniques to define a sample of informal leaders similar to the Bureau nominees without having to explicitly

The OSACA architecture allows the assembly of the machine tool control using a user interface, without the need to review the whole software (Altintas, et al., 1996).. To reach this

Classical tools for the analysis of structured data are, for example, Online Analytical Processing (OLAP), querying and reporting [24] and will mainly be used in

• VISUALIZE (generally in 2D) the distribution of data with a topology-preserving “projection” (2 points close in input space should be projected on close cells on the SOM).

Statistical Machine-Learning: framework + supervised ML, Pr Fabien MOUTARDE, Center for Robotics, MINES ParisTech, PSL, Nov.2018 1..