Opendata, web and dolomites

Re-SENSE SIGNED

RESOURCE-EFFICIENT SENSING THROUGH DYNAMIC ATTENTION-SCALABILITY

Total Cost €

0

EC-Contrib. €

0

Partnership

0

Views

0

 Re-SENSE project word cloud

Explore the words cloud of the Re-SENSE project. It provides you a very rough idea of what is the project "Re-SENSE" about.

nowadays    talk    hardware    massive    berkeley    gained    maximize    combined    intel    streams    cell    epilepsy    coming    constrained    tasting    efficiency    sense    stand    masters    resource    electronics    combine    maximum    bandwidth    critical    kuleuven    capabilities    sensors    labs    seamlessly    implementing    function    expertise    throughput    learning    processors    wearables    fuse    human    scalability    humans    perfectly    observe    re    data    demonstrated    tuning    limited    eyes    understand    drastically    memory    sorting    rigid    had    leg    algorithms    senses    dynamic    scalable    uc    lips    jointly    latency    robotics    judgements    close    sensor    capture    preventing    extract    monitoring    it    interfacing    hard    fusion    sensing    trouble    food    inference    machine    smelling    dynamically    sensory    levels    devote    workloads    energy    fits    computational    processor    mental    always    reconfigurable    people    pi    effort    few    biomedical    intriguingly    equipped    combination    amount    scarce   

Project "Re-SENSE" data sheet

The following table provides information about the project.

Coordinator
KATHOLIEKE UNIVERSITEIT LEUVEN 

Organization address
address: OUDE MARKT 13
city: LEUVEN
postcode: 3000
website: www.kuleuven.be

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Belgium [BE]
 Total cost 1˙484˙562 €
 EC max contribution 1˙484˙562 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2016-STG
 Funding Scheme ERC-STG
 Starting year 2017
 Duration (year-month-day) from 2017-03-01   to  2022-02-28

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    KATHOLIEKE UNIVERSITEIT LEUVEN BE (LEUVEN) coordinator 1˙484˙562.00

Map

 Project objective

It is hard to stand on one leg if we close our eyes. We have trouble tasting food without smelling. And when we talk with other people, we observe their lips to understand them better. We, humans, are masters in sensor fusion as we can seamlessly combine information coming from different senses to improve our judgements. Intriguingly, in order to fuse information efficiently, we do not always devote the same level of attention or mental effort to each of the many sensory streams available to us. This dynamic attention-scalability allows us to always extract the maximum amount of relevant information under our limited human computational bandwidth.

Would it not be great if electronics had the same capabilities? While many devices are nowadays equipped with a massive amount of sensors, they typically cannot effectively fuse more than a few of them. The rigid way in which sensory data is combined results in large computational workloads, preventing effective multi-sensor fusion in resource-constrained applications such as robotics, wearables, biomedical monitoring or user interfacing.

The Re-SENSE project will bring attention-scalable sensing to resource-scarce devices, which are constrained in terms of energy, throughput, latency or memory resources. This is achieved by jointly: 1) Developing resource-aware inference and fusion algorithms, which maximize information capture in function of hardware resource usage, dynamically tuning sensory attention levels 2) Implementing dynamic, wide-range resource-scalable inference processors, allowing to exploit this attention-scalability for drastically improved efficiency The attention-scalable sensing concept will be demonstrated in 2 highly resource-constrained applications: a) latency-critical cell sorting and b) energy-critical epilepsy monitoring. This combination of processor design, reconfigurable hardware and embedded machine learning fits perfectly to the PI’s expertise gained at Intel Labs, UC Berkeley and KULeuven.

 Publications

year authors and title journal last update
List of publications.
2019 L Galindez Olascoaga, W. Meert, M. Verhelst, G. Van den Broeck
Towards Hardware-Aware Tractable Learning of Probabilistic Models (workshop version)
published pages: , ISSN: , DOI:
3rd Tractable Probabilistic Modeling Workshop colocated with the 36th International Conference on Machine Learning (TPM-ICML 2019) 2019-11-08
2019 Nimish Shah, Laura I. Galindez Olascoaga, Wannes Meert and Marian Verhelst
PRU: Probabilistic Reasoning processing Unit for resource-efficient AI
published pages: , ISSN: , DOI:
HotChips 2019-10-29
2017 Marian Verhelst, Bert Moons
Embedded Deep Neural Network Processing: Algorithmic and Processor Techniques Bring Deep Learning to IoT and Edge Devices
published pages: 55-65, ISSN: 1943-0582, DOI: 10.1109/mssc.2017.2745818
IEEE Solid-State Circuits Magazine 9/4 2019-10-29
2019 Laura I. Galindez Olascoaga, Wannes Meert, Nimish Shah, Marian Verhelst, Guy Van den Broeck
Towards Hardware-Aware Tractable Learning of Probabilistic Models
published pages: , ISSN: , DOI:
Accepted for Publication at Proceedings of the Thirty-third Conference on Neural Information Processing Systems (NeurIPS 2019). 2019-10-29
2018 Thomas Bos, Komail Badami, Wim Dehaene, Marian Verhelst
Architecture optimization for energy-efficient resolution-scalable 8–12-bit SAR ADCs
published pages: 437-448, ISSN: 0925-1030, DOI: 10.1007/s10470-018-1235-0
Analog Integrated Circuits and Signal Processing 97/3 2019-10-29
2018 Laura Galindez, Komail Badami, Jonas Vlasselaer, Wannes Meert, Marian Verhelst
Dynamic Sensor-Frontend Tuning for Resource Efficient Embedded Classification
published pages: 1-1, ISSN: 2156-3357, DOI: 10.1109/JETCAS.2018.2850451
IEEE Journal on Emerging and Selected Topics in Circuits and Systems 2019-06-13
2018 Thomas Bos, Komail Badami, Wim Dehaene, Marian Verhelst
Architecture optimization for energy-efficient resolution-scalable 8–12-bit SAR ADCs
published pages: , ISSN: 0925-1030, DOI: 10.1007/s10470-018-1235-0
Analog Integrated Circuits and Signal Processing 2019-06-13
2018 Koen Goetschalckx, Bert Moons, Steven Lauwereins, Martin Andraud, Marian Verhelst
Optimized Hierarchical Cascaded Processing
published pages: 1-1, ISSN: 2156-3357, DOI: 10.1109/JETCAS.2018.2839347
IEEE Journal on Emerging and Selected Topics in Circuits and Systems 2019-06-13

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "RE-SENSE" project.

For instance: the website url (it has not provided by EU-opendata yet), the logo, a more detailed description of the project (in plain text as a rtf file or a word file), some pictures (as picture files, not embedded into any word file), twitter account, linkedin page, etc.

Send me an  email (fabio@fabiodisconzi.com) and I put them in your project's page as son as possible.

Thanks. And then put a link of this page into your project's website.

The information about "RE-SENSE" are provided by the European Opendata Portal: CORDIS opendata.

More projects from the same programme (H2020-EU.1.1.)

evolSingleCellGRN (2019)

Constraint, Adaptation, and Heterogeneity: Genomic and single-cell approaches to understanding the evolution of developmental gene regulatory networks

Read More  

IMMUNOTHROMBOSIS (2019)

Cross-talk between platelets and immunity - implications for host homeostasis and defense

Read More  

RODRESET (2019)

Development of novel optogenetic approaches for improving vision in macular degeneration

Read More