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pro vyhledávání: '"Frischknecht, Adrian"'
Autor:
Lübeck, Konstantin, Jung, Alexander Louis-Ferdinand, Wedlich, Felix, Müller, Mika Markus, Peccia, Federico Nicolás, Thömmes, Felix, Steinmetz, Jannik, Biermaier, Valentin, Frischknecht, Adrian, Bernardo, Paul Palomero, Bringmann, Oliver
Implementing Deep Neural Networks (DNNs) on resource-constrained edge devices is a challenging task that requires tailored hardware accelerator architectures and a clear understanding of their performance characteristics when executing the intended A
Externí odkaz:
http://arxiv.org/abs/2409.08595
Hardware Accelerator and Neural Network Co-Optimization for Ultra-Low-Power Audio Processing Devices
Autor:
Gerum, Christoph, Frischknecht, Adrian, Hald, Tobias, Bernardo, Paul Palomero, Lübeck, Konstantin, Bringmann, Oliver
The increasing spread of artificial neural networks does not stop at ultralow-power edge devices. However, these very often have high computational demand and require specialized hardware accelerators to ensure the design meets power and performance
Externí odkaz:
http://arxiv.org/abs/2209.03807
Publikováno v:
ICANN 2021. Lecture Notes in Computer Science, vol 12891, pp 369-378. Springer
Keyword spotting (KWS) is becoming a ubiquitous need with the advancement in artificial intelligence and smart devices. Recent work in this field have focused on several different architectures to achieve good results on datasets with low to moderate
Externí odkaz:
http://arxiv.org/abs/2109.07930
Akademický článek
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Dieses Buch bietet eine Einführung in die wichtigsten Themen rund um Eingebettete Systeme wie zum Beispiel Technologien, Entwicklungsmethodik, Modelle, Eingebettete KI-Systeme, Systembeschreibungssprachen, Hardware-Synthese, Kommunikation und Netzwe
The proceedings set LNCS 12891, LNCS 12892, LNCS 12893, LNCS 12894 and LNCS 12895 constitute the proceedings of the 30th International Conference on Artificial Neural Networks, ICANN 2021, held in Bratislava, Slovakia, in September 2021.• The total