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Brain-inspired Computing and Machine Learning (editorial)
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SYSNO ASEP 0523724 Document Type J - Journal Article R&D Document Type O - Ostatní Subsidiary J Článek ve WOS Title Brain-inspired Computing and Machine Learning (editorial) Author(s) Iliadis, L. (GR)
Kůrková, Věra (UIVT-O) RID, SAI, ORCID
Hammer, B. (DE)Source Title Neural Computing & Applications. - : Springer - ISSN 0941-0643
Roč. 32, č. 11 (2020), s. 6641-6643Number of pages 3 s. Publication form Print - P Language eng - English Country GB - United Kingdom Keywords editorial ; brain-inspired computing Subject RIV IN - Informatics, Computer Science OECD category Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) Method of publishing Open access Institutional support UIVT-O - RVO:67985807 UT WOS 000523105100002 EID SCOPUS 85082936460 DOI 10.1007/s00521-020-04888-6 Annotation IN: 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. Workplace Institute of Computer Science Contact Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800 Year of Publishing 2021 Electronic address http://dx.doi.org/10.1007/s00521-020-04888-6
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