Publication Details

Acceleration Techniques for Automated Design of Approximate Convolutional Neural Networks

PIŇOS Michal, MRÁZEK Vojtěch, VAVERKA Filip, VAŠÍČEK Zdeněk and SEKANINA Lukáš. Acceleration Techniques for Automated Design of Approximate Convolutional Neural Networks. IEEE Journal on Emerging and Selected Topics in Circuits and Systems, vol. 13, no. 1, 2023, pp. 212-224. ISSN 2156-3357. Available from: https://ieeexplore.ieee.org/document/10011413
Type
journal article
Language
english
Authors
Piňos Michal, Ing. (DCSY FIT BUT)
Mrázek Vojtěch, Ing., Ph.D. (DCSY FIT BUT)
Vaverka Filip, Ing. (DCSY FIT BUT)
Vašíček Zdeněk, doc. Ing., Ph.D. (DCSY FIT BUT)
Sekanina Lukáš, prof. Ing., Ph.D. (DCSY FIT BUT)
URL
Published
2023
Pages
212-224
Journal
IEEE Journal on Emerging and Selected Topics in Circuits and Systems, vol. 13, no. 1, ISSN 2156-3357
Publisher
IEEE Circuits and Systems Society
DOI
10.1109/JETCAS.2023.3235204
BibTeX 
@ARTICLE{FITPUB12665,
   author = "Michal Pi\v{n}os and Vojt\v{e}ch Mr\'{a}zek and Filip Vaverka and Zden\v{e}k Va\v{s}\'{i}\v{c}ek and Luk\'{a}\v{s} Sekanina",
   title = "Acceleration Techniques for Automated Design of Approximate Convolutional Neural Networks",
   pages = "212--224",
   journal = "IEEE Journal on Emerging and Selected Topics in Circuits and Systems",
   volume = 13,
   number = 1,
   year = 2023,
   ISSN = "2156-3357",
   doi = "10.1109/JETCAS.2023.3235204",
   language = "english",
   url = "https://www.fit.vut.cz/research/publication/12665"
}
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