Details

Autor(en) / Beteiligte

• Aichroth, Patrick
• Antes, Christoph
• Gembatzka, Pierre
• Graf, Holger
• Johnson, David S.
• Jung, Matthias
• Kämpfe, Thomas
• Kleinberger, Thomas
• Köllmer, Thomas
• Kuhn, Thomas
• Kutter, Christoph
• Krüger, Jens
• Loroch, Dominik M.
• Lukashevich, Hanna
• Laleni, Nellie
• Zhang, Lei
• Leugering, Johannes
• Martín Fernández, Rodrigo
• Mateu, Loreto
• Mojumder, Shaown
• Prautsch, Benjamin
• Pscheidl, Ferdinand
• Roscher, Karsten
• Schneickert, Sören
• Vanselow, Frank
• Wallbott, Paul
• Walter, Oliver
• Weber, Nico

Titel

SEC-Learn: Sensor Edge Cloud for Federated Learning: Invited Paper

Ist Teil von

• Embedded Computer Systems: Architectures, Modeling, and Simulation, p.432-448

Ort / Verlag

Cham: Springer International Publishing

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• Due to the slow-down of Moore’s Law and Dennard Scaling, new disruptive computer architectures are mandatory. One such new approach is Neuromorphic Computing, which is inspired by the functionality of the human brain. In this position paper, we present the projected SEC-Learn ecosystem, which combines neuromorphic embedded architectures with Federated Learning in the cloud, and performance with data protection and energy efficiency.