bookchapters.bib

@incollection{ZesBelFraRigLam22-MLNVM-BC,
  author = {Zese, Riccardo and Bellodi, Elena and Fraccaroli, Michele and Riguzzi, Fabrizio and Lamma, Evelina},
  editor = {Micheloni, Rino and Zambelli, Cristian},
  title = {Neural Networks and Deep Learning Fundamentals},
  booktitle = {Machine Learning and Non-volatile Memories},
  year = {2022},
  publisher = {Springer International Publishing},
  address = {Cham},
  pages = {23--42},
  abstract = {In the last decade, Neural Networks (NNs) have come to the fore as one of the most powerful and versatile approaches to many machine learning tasks. Deep Learning (DL)Deep Learning (DL), the latest incarnation of NNs, is nowadays applied in every scenario that needs models able to predict or classify data. From computer vision to speech-to-text, DLDeep Learning (DL) techniques are able to achieve super-human performance in many cases. This chapter is devoted to give a (not comprehensive) introduction to the field, describing the main branches and model architectures, in order to try to give a roadmap of this area to the reader.},
  isbn = {978-3-031-03841-9},
  doi = {10.1007/978-3-031-03841-9_2},
  url = {https://doi.org/10.1007/978-3-031-03841-9_2}
}

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