Počet záznamů: 1  

Brain-inspired Computing and Machine Learning (editorial)

  1. 1.
    SYSNO ASEP0523724
    Druh ASEPJ - Článek v odborném periodiku
    Zařazení RIVO - Ostatní
    Poddruh JČlánek ve WOS
    NázevBrain-inspired Computing and Machine Learning (editorial)
    Tvůrce(i) Iliadis, L. (GR)
    Kůrková, Věra (UIVT-O) RID, SAI, ORCID
    Hammer, B. (DE)
    Zdroj.dok.Neural Computing & Applications. - : Springer - ISSN 0941-0643
    Roč. 32, č. 11 (2020), s. 6641-6643
    Poč.str.3 s.
    Forma vydáníTištěná - P
    Jazyk dok.eng - angličtina
    Země vyd.GB - Velká Británie
    Klíč. slovaeditorial ; brain-inspired computing
    Vědní obor RIVIN - Informatika
    Obor OECDComputer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
    Způsob publikováníOpen access
    Institucionální podporaUIVT-O - RVO:67985807
    UT WOS000523105100002
    EID SCOPUS85082936460
    DOI10.1007/s00521-020-04888-6
    AnotaceIN: Neural Computing & Applications. 2020, 32(11), 6641-6643. ISSN 0941-0643. doi: 10.1007/s00521-020-04888-6. ANNOTATION: Recent research in machine learning (ML) and neurophysiology has focused in the development of highly intelligent algorithms, utilizing information processing principles of the human brain. Deep learning is inspired by the architecture of the cerebral cortex and it has attracted the attention of many artificial intelligence (AI) scientists. It is the dominating AI approach in specific domains (e.g., image–voice classification, object detection) regardless of its requirements in high computational power and in high volume of data. This is the editorial of the “Brain Inspired Computing and Machine Learning” Special Issue (SI) of the Neural Computing and Applications Springer Journal. The response of the scientific community has been significant, as many original research papers have been submitted for consideration. Totally, 11 papers were accepted out of 20, after going through a peer-review process. All of them have significant elements of novelty and they are introducing interesting modeling approaches or algorithms, inspired by the biological processes of the human brain.
    PracovištěÚstav informatiky
    KontaktTereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800
    Rok sběru2021
    Elektronická adresahttp://dx.doi.org/10.1007/s00521-020-04888-6
Počet záznamů: 1  

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