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.

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

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.)

ENTRAPMENT (2019)

Septins: from bacterial entrapment to cellular immunity

Read More  

EVOCELFATE (2019)

Evolution of cell fate specification modes in spiral cleavage

Read More  

SLAMseq (2019)

SLAMseq: Temporal resolution in gene expression profiling across multiple platforms

Read More