Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Peccia, Federico"'
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
During the last years, algorithms known as Convolutional Neural Networks (CNNs) had become increasingly popular, expanding its application range to several areas. In particular, the image processing field has experienced a remarkable advance thanks t
Externí odkaz:
http://arxiv.org/abs/2408.14055
The growing concerns regarding energy consumption and privacy have prompted the development of AI solutions deployable on the edge, circumventing the substantial CO2 emissions associated with cloud servers and mitigating risks related to sharing sens
Externí odkaz:
http://arxiv.org/abs/2408.07404
Embedded distributed inference of Neural Networks has emerged as a promising approach for deploying machine-learning models on resource-constrained devices in an efficient and scalable manner. The inference task is distributed across a network of emb
Externí odkaz:
http://arxiv.org/abs/2405.03360
Model compression and hardware acceleration are essential for the resource-efficient deployment of deep neural networks. Modern object detectors have highly interconnected convolutional layers with concatenations. In this work, we study how pruning c
Externí odkaz:
http://arxiv.org/abs/2405.03715