Hardware-aware comparative study of lightweight convolutional neural networks for Raspberry Pi-based autonomous driving.

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Title: Hardware-aware comparative study of lightweight convolutional neural networks for Raspberry Pi-based autonomous driving.
Authors: Kim, Hyung In1, khi103@yonsei.ac.kr, Park, Youngmin2, ympillow@sookmyung.ac.kr
Source: International Journal of Electrical & Computer Engineering (2088-8708); Jun2026, Vol. 16 Issue 3, p1493-1507, 15p
Database: Applied Science & Technology Source
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DbLabel: Applied Science & Technology Source
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PubType: Academic Journal
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  Data: Hardware-aware comparative study of lightweight convolutional neural networks for Raspberry Pi-based autonomous driving.
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  Data: <searchLink fieldCode="AU" term="%22Kim%2C+Hyung+In%22">Kim, Hyung In</searchLink><relatesTo>1</relatesTo>, <i>khi103@yonsei.ac.kr</i><br /><searchLink fieldCode="AU" term="%22Park%2C+Youngmin%22">Park, Youngmin</searchLink><relatesTo>2</relatesTo>, <i>ympillow@sookmyung.ac.kr</i>
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PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=194285636
RecordInfo BibRecord:
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      – Type: doi
        Value: 10.11591/ijece.v16i3.pp1493-1507
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      – Code: eng
        Text: English
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      Pagination:
        PageCount: 15
        StartPage: 1493
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      – TitleFull: Hardware-aware comparative study of lightweight convolutional neural networks for Raspberry Pi-based autonomous driving.
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            NameFull: Kim, Hyung In
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            NameFull: Park, Youngmin
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            – D: 01
              M: 06
              Text: Jun2026
              Type: published
              Y: 2026
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