Opendata, web and dolomites

MAJORIS SIGNED

Majoration-Minimization algorithms for Image Processing

Total Cost €

0

EC-Contrib. €

0

Partnership

0

Views

0

 MAJORIS project word cloud

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

tackle    reducing    super    action    structure    robustness    concerning    imaging    breakthrough    microscopy    changing    multiphoton    spectrometry    acceleration    proved    designed    instruments    resolution    parallel    acquisition    medicine    limiting    techniques    signal    datasets    too    amounts    science    employed    practical    consist    mind    solved    biology    relatively    optimization    solving    variables    domain    strategies    tomosynthesis    class    proposing    sophisticated    inexact    minimizing    minimization    constantly    fly    chemistry    tools    convergence    physical    collected    3d    implementations    foundations    mathematical    quality    play    computational    theoretical    versatility    big    medical    schemes    data    function    mass    distributed    algorithms    majorization    obey    least    scalability    rudimentary    efficient    context    algorithm    image    majoris    mm    observation    questions    numerical    astronomy    outcomes    load    handling    solid    analytically    massively    dealing    benefit    physics    reconstruction    breast    architecture   

Project "MAJORIS" data sheet

The following table provides information about the project.

Coordinator
INSTITUT NATIONAL DE RECHERCHE ENINFORMATIQUE ET AUTOMATIQUE 

Organization address
address: DOMAINE DE VOLUCEAU ROCQUENCOURT
city: LE CHESNAY CEDEX
postcode: 78153
website: www.inria.fr

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 France [FR]
 Total cost 1˙500˙000 €
 EC max contribution 1˙500˙000 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2019-STG
 Funding Scheme ERC-STG
 Starting year 2020
 Duration (year-month-day) from 2020-01-01   to  2024-12-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    INSTITUT NATIONAL DE RECHERCHE ENINFORMATIQUE ET AUTOMATIQUE FR (LE CHESNAY CEDEX) coordinator 1˙500˙000.00

Map

 Project objective

Mathematical optimization is the key to solving many problems in science, based on the observation that physical systems obey a general principle of least action. While some problems can be solved analytically, many more can only be solved via numerical algorithms. Research in this domain has proved essential over many years. In addition, science in general is changing. Increasingly, in biology, medicine, astronomy, chemistry, physics, large amounts of data are collected by constantly improving signal and image acquisition devices, that must be analyzed by sophisticated optimization tools. In this proposal, we consider handling optimization problems with large datasets. This means minimizing a cost function with a complex structure and many variables. The computational load for solving these problems is too great for even state-of-the-art algorithms. Thus, only relatively rudimentary data processing techniques are employed, reducing the quality of the results and limiting the outcomes that can be achieved via these novel instruments. New algorithms must be designed with computational scalability, robustness and versatility in mind. In this context, Majorization-Minimization (MM) approaches have a crucial role to play. They consist of a class of efficient and effective optimization algorithms that benefit from solid theoretical foundations. The MAJORIS project aims at proposing a breakthrough in MM algorithms, so that they remain efficient when dealing with big data. I propose to tackle several challenging questions concerning algorithm design. These include acceleration strategies, convergence analysis with complex costs and inexact schemes. I will also tackle practical, massively parallel and distributed architecture implementations. Three specific applications are targeted: super-resolution in multiphoton microscopy in biology; on-the-fly reconstruction for 3D breast tomosynthesis in medical imaging; and mass spectrometry data processing in chemistry.

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "MAJORIS" 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 "MAJORIS" are provided by the European Opendata Portal: CORDIS opendata.

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

Aware (2019)

Aiding Antibiotic Development with Deep Analysis of Resistance Evolution

Read More  

CARBYNE (2020)

New carbon reactivity rules for molecular editing

Read More  

ENUF (2019)

Evaluation of Novel Ultra-Fast selective III-V Epitaxy

Read More