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دسته بندی:
هوش مصنوعی - Artificial intelligence
سال انتشار:
2020
عنوان انگلیسی مقاله:
AITIA: Embedded AI Techniques for Embedded Industrial Applications
ترجمه فارسی عنوان مقاله:
AITIA: تکنیک های هوش مصنوعی جاسازی شده برای کاربردهای صنعتی جاسازی شده
منبع:
IEEE - 2020 International Conference on Omni-layer Intelligent Systems (COINS);2020; ; ;
نویسنده:
Marcelo Brandalero1, Muhammad Ali2, Laurens Le Jeune3, Hector Gerardo Mu˜noz Hernandez1, Mitko Veleski1, Bruno da Silva45, Jan Lemeire45, Kristof Van Beeck3, Abdellah Touhafi45, Toon Goedem´e3, Nele Mentens3, Diana G¨ohringer2, Michael H¨ubner1
چکیده انگلیسی:
New achievements in Artificial Intelligence (AI)
and Machine Learning (ML) are reported almost daily by the
big companies. While those achievements are accomplished by
fast and massive data processing techniques, the potential of
embedded machine learning, where intelligent algorithms run
in resource-constrained devices rather than in the cloud, is still
not understood well by the majority of the industrial players
and Small and Medium Entereprises (SMEs). Nevertheless,
the potential embedded machine learning for processing highperformance
algorithms without relying on expensive cloud solutions
is perceived as very high. This potential has led to a broad
demand by industry and SMEs for a practical and applicationoriented
feasibility study, which helps them to understand the
potential benefits, but also the limitations of embedded AI. To
address these needs, this paper presents the approach of the
AITIA project, a consortium of four Universities which aims at
developing and demonstrating best practices for embedded AI
by means of four industrial case studies of high-relevance to the
European industry and SMEs: sensors, security, automotive and
industry 4.0.
Index Terms: artificial intelligence | machine learning | embedded hardware | sensors | network intrusion detection | driver assistance | industry 4.0
قیمت: رایگان
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