期刊
35TH INTERNATIONAL CONFERENCE ON INFORMATION NETWORKING (ICOIN 2021)
卷 -, 期 -, 页码 514-516出版社
IEEE
DOI: 10.1109/ICOIN50884.2021.9333967
关键词
Artificial Intelligence; Face Recognition; Neuromorphic; NeruoEdge; NM500
类别
资金
- National Research Foundation of Korea(NRF) - Ministry of Education [2019R1I1A1A01063895, 2018R1A6A1A03024003]
- Grand Information Technology Research Center Program through the Institute of Information & Communications Technology and Planning & Evaluation (IITP) - Ministry of Science and ICT (MSIT), Korea [IITP-2020-2020-0-01612]
- Institute for Information & Communication Technology Planning & Evaluation (IITP), Republic of Korea [2020-0-01612-002] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
- National Research Foundation of Korea [2018R1A6A1A03024003, 2019R1I1A1A01063895] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
This paper discusses intelligent edge computing technology using neuromorphic technology, showcasing the performance through a face recognition test. Results demonstrate that neuromorphic technology, such as the NM500 chip, can reduce training time and does not require a large number of datasets for effective training.
This paper discusses intelligent edge computing technology using neuromorphic technology. Neuromorphic is a technology that uses pure hardware to implement intelligent systems, unlike traditional methods of implementing intelligent systems in a software manner using CPU or GPU hardware. In this paper, intelligent edge computing technology was introduced using NeuroEdge, one of the devices using Neurologic technology, and the performance was verified through a face recognition test. Results showed that using neuromorphic technology such as the NM500 chip saves the time needed for training systems and does not impose the burden of requiring many datasets for effective training.
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