Zobrazeno 1 - 10
of 48
pro vyhledávání: '"Lukas Cavigelli"'
Autor:
Andrin Caviezel, Adrian Ringenbach, Sophia E. Demmel, Claire E. Dinneen, Nora Krebs, Yves Bühler, Marc Christen, Guillaume Meyrat, Andreas Stoffel, Elisabeth Hafner, Lucie A. Eberhard, Daniel von Rickenbach, Kevin Simmler, Philipp Mayer, Pascal S. Niklaus, Thomas Birchler, Tim Aebi, Lukas Cavigelli, Michael Schaffner, Stefan Rickli, Christoph Schnetzler, Michele Magno, Luca Benini, Perry Bartelt
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-9 (2021)
The awareness of rock shape dependence in rockfall hazard assessment is growing, but experimental and field studies are scarce. This study presents a large data set of induced single block rockfall events quantifying the influence of rock shape and m
Externí odkaz:
https://doaj.org/article/10ef258739ba49e9b175376cea51a45c
Autor:
Michele Magno, Lukas Sigrist, Andres Gomez, Lukas Cavigelli, Antonio Libri, Emanuel Popovici, Luca Benini
Publikováno v:
Sensors, Vol 19, Iss 12, p 2747 (2019)
We report on a self-sustainable, wireless accelerometer-based system for wear detection in a band saw blade. Due to the combination of low power hardware design, thermal energy harvesting with a small thermoelectric generator (TEG), an ultra-low powe
Externí odkaz:
https://doaj.org/article/5abdb88cb09747b7af2667d10a893f54
Publikováno v:
IEEE Transactions on Biomedical Circuits and Systems. 15:1149-1160
Motor imagery (MI) brain-machine interfaces (BMIs) enable us to control machines by merely thinking of performing a motor action. Practical use cases require a wearable solution where the classification of the brain signals is done locally near the s
Vector architectures are gaining traction for highly efficient processing of data-parallel workloads, driven by all major ISAs (RISC-V, Arm, Intel), and boosted by landmark chips, like the Arm SVE-based Fujitsu A64FX, powering the TOP500 leader Fugak
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1cf89df1bb56c85e8668eb14a8d5d447
http://arxiv.org/abs/2210.08882
http://arxiv.org/abs/2210.08882
Most of today's computer vision pipelines are built around deep neural networks, where convolution operations require most of the generally high compute effort. The Winograd convolution algorithm computes convolutions with fewer MACs compared to the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2d9cefb03e24cd921a32774bada908fd
http://arxiv.org/abs/2209.12982
http://arxiv.org/abs/2209.12982
Publikováno v:
2022 IEEE 4th International Conference on Artificial Intelligence Circuits and Systems (AICAS).
Publikováno v:
IEEE Transactions on Circuits and Systems I: Regular Papers, 69 (1)
Recurrent neural networks such as Long Short-Term Memories (LSTMs) learn temporal dependencies by keeping an internal state, making them ideal for time-series problems such as speech recognition. However, the output-to-input feedback creates distinct
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f6a284543fa44e69a935ee479e9f63a9
http://arxiv.org/abs/2202.07462
http://arxiv.org/abs/2202.07462
Autor:
Gianmarco Cerutti, Lukas Cavigelli, Renzo Andri, Michele Magno, Elisabetta Farella, Luca Benini
Keyword spotting (KWS) is a crucial function enabling the interaction with the many ubiquitous smart devices in our surroundings, either activating them through wake-word or directly as a human-computer interface. For many applications, KWS is the en
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1f91b9b0642b1ee1f55ce6aaef1320e9
Autor:
Xavier Timoneda, Lukas Cavigelli
Publikováno v:
DAC
Logic optimization is an NP-hard problem commonly approached through hand-engineered heuristics. We propose to combine graph convolutional networks with reinforcement learning and a novel, scalable node embedding method to learn which local transform
Publikováno v:
ISCAS
With Motor-Imagery (MI) Brain-Machine Interfaces (BMIs) we may control machines by merely thinking of performing a motor action. Practical use cases require a wearable solution where the classification of the brain signals is done locally near the se