Deep Learning

@article{Schulz2012DeepL,
  title={Deep Learning},
  author={Hannes Schulz and Sven Behnke},
  journal={KI - K{\"u}nstliche Intelligenz},
  year={2012},
  volume={26},
  pages={357-363}
}
Hierarchical neural networks for object recognition have a long history. In recent years, novel methods for incrementally learning a hierarchy of features from unlabeled inputs were proposed as good starting point for supervised training. These deep learning methods—together with the advances of parallel computers—made it possible to successfully attack problems that were not practical before, in terms of depth and input size. In this article, we introduce the reader to the basic concepts of… Expand
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