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INTESA 2018 : INTelligent Embedded Systems Architectures and Applications

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Link: http://intesa-workshop2018.polimi.it/
 
When Sep 30, 2018 - Oct 5, 2018
Where Turin, Italy
Submission Deadline Jul 10, 2018
Notification Due Aug 10, 2018
Final Version Due Aug 30, 2018
Categories    IOT   computer architectures   embedded systems   deep learning
 

Call For Papers

The INTESA workshop aims to give an up-to-date picture of intelligent embedded systems architectures and applications with emphasis on Smart IoT and Cyber Physical Systems, including hot topics such as accelerating deep learning. The workshop covers several aspects, from the hardware related ones to embedded software and application issues, being complementary to most of the topic addressed during the ESWEEK. From the market standpoint, scientific progress in this field are considered crucial to fuel a widespread diffusion of the potential benefits offered by the Industry 4.0 perspective. The goal of the event is to create cross-fertilization of ideas between application developers and platform providers with the participation of a mix between academic and industry people.

The workshop is organized in two sessions: 1) “Architectures and design methodologies to support embedded intelligence”, 2) “Embedded Intelligence: best practices and software support” and it includes: 2 keynote speakers, 4 invited papers and 6 regular papers for an exciting full-immersion day.

A non-exhaustive list of suggested topics for paper submission are the following ones. However, other submissions in line with the workshop objectives are welcome:
* Special purpose hardware to support deep learning in embedded architectures
* Edge computing for smart embedded systems: hardware and software aspects
* Run-time resource management for smart IoT/Edge Computing systems
* HW/SW codesign of Cyber Physical Systems
* Programming models for IoT/Edge computing applications
* Applications and case studies of intelligent embedded systems
* Design methodologies and platforms for wearable computing
* In-memory computing for unsupervised learning

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