An overview of deep learning techniques

Deep learning is the paradigm that profoundly changed the artificial intelligence landscape within only a few years. Although accompanied by a variety of algorithmic achievements, this technology is disruptive mainly from the application perspective: It considerably pushes the border of tasks that c...

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Bibliographic Details
Published inAutomatisierungstechnik : AT Vol. 66; no. 9; pp. 690 - 703
Main Author Vogt, Michael
Format Journal Article
LanguageEnglish
Published De Gruyter Oldenbourg 25.09.2018
Subjects
artificial intelligence
deep learning
end-to-end learning
Künstliche Intelligenz
neural networks
Neuronale Netze
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Summary:Deep learning is the paradigm that profoundly changed the artificial intelligence landscape within only a few years. Although accompanied by a variety of algorithmic achievements, this technology is disruptive mainly from the application perspective: It considerably pushes the border of tasks that can be automated, changes the way products are developed, and is available to virtually everyone. Subject of deep learning are artificial neural networks with a large number of layers. Compared to earlier approaches with ideally a single layer, this allows using massive computational resources to train black-box models directly on raw data with a minimum of engineering work. Most successful applications are found in visual image understanding, but also in audio and text modeling.
ISSN:0178-2312
2196-677X
DOI:10.1515/auto-2018-0076