
INTESA@ESWEEK 2018: Torino, Italy
- Maurizio Martina, William Fornaciari:
Proceedings of the Workshop on INTelligent Embedded Systems Architectures and Applications, INTESA@ESWEEK 2018, Turin, Italy, October 04-04, 2018. ACM 2018, ISBN 978-1-4503-6598-7
Architectures and design methodologies to support embedded intelligence
- Paulo Cesar Santos, João Paulo C. de Lima, Rafael Fão de Moura, Hameeza Ahmed, Marco A. Z. Alves
, Antonio C. S. Beck, Luigi Carro:
Exploring IoT platform with technologically agnostic processing-in-memory framework. 1-6 - Nadir Cherifi, Alexandre Boe
, Thomas Vantroys, Colombe Herault, Gilles Grimaud:
A low-cost energy consumption measurement platform. 7-12 - Alberto Marchisio, Rachmad Vidya Wicaksana Putra
, Muhammad Abdullah Hanif, Muhammad Shafique
:
HW/SW co-design and co-optimizations for deep learning. 13-18
Embedded Intelligence: best practices and software support
- Paolo Meloni
, Daniela Loi
, Gianfranco Deriu, Andy D. Pimentel, Dolly Sapra, Bernhard Moser, Natalia Shepeleva, Francesco Conti, Luca Benini
, Oscar Ripolles
, David Solans, Maura Pintor, Battista Biggio
, Todor P. Stefanov, Svetlana Minakova, Nikolaos Fragoulis, Ilias Theodorakopoulos
, Michael Masin, Francesca Palumbo:
ALOHA: an architectural-aware framework for deep learning at the edge. 19-26 - Flávia Pisani
, Edson Borin:
Fog vs. cloud computing: should i stay or should i go? 27-32 - Michele Zanella, Giuseppe Massari
, Andrea Galimberti, William Fornaciari
:
Back to the future: resource management in post-cloud solutions. 33-38 - Charalampos Marantos, Christos P. Lamprakos, Vasileios Tsoutsouras, Kostas Siozios, Dimitrios Soudris:
Towards plug&play smart thermostats inspired by reinforcement learning. 39-44 - Matteo Grimaldi, Federico Pugliese, Valerio Tenace, Andrea Calimera
:
A compression-driven training framework for embedded deep neural networks. 45-50
Posters
- Nicholas Mainardi, Michele Zanella, Federico Reghenzani
, Niccoló Raspa, Carlo Brandolese:
An unsupervised approach for automotive driver identification. 51-52 - Jae-Yun Kim, Soo-Mook Moon:
Blockchain-based edge computing for deep neural network applications. 53-55

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