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DEXIM SIGNED

Deeply Explainable Intelligent Machines

Total Cost €

0

EC-Contrib. €

0

Partnership

0

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 DEXIM project word cloud

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

opaque    automatic    situations    warn    supports    stable    domain    monitoring    patients    hence    incorporate    frequently    adaptive    human    operate    building    prevent    positive    justify    imagery    vehicles    makers    driving    strengthen    data    direct    critical    industry    humans    lives    continuity    gdpr    millions    deep    mechanisms    practical    ultimately    put    scene    language    justifying    decisions    collaborate    fail    multiple    save    law    satellite    explainable    transparent    unable    explanation    scaffold    intelligent    visual    maker    themselves    arise    market    easily    memory    wrong    ailment    adapt    robotics    medical    modalities    temporal    trust    mobile    self    decision    explanatory    learning    machine    attain    monitor    explanations    fashioned    concerning    interactions    hurricane    constraints    led    abnormal    world    environment    possibility    valuable    point    output    natural    competitive    position    trainable    notably    artificially    contrast   

Project "DEXIM" data sheet

The following table provides information about the project.

Coordinator
EBERHARD KARLS UNIVERSITAET TUEBINGEN 

Organization address
address: GESCHWISTER-SCHOLL-PLATZ
city: TUEBINGEN
postcode: 72074
website: www.uni-tuebingen.de

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 Germany [DE]
 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 2019
 Duration (year-month-day) from 2019-12-01   to  2024-11-30

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    EBERHARD KARLS UNIVERSITAET TUEBINGEN DE (TUEBINGEN) coordinator 1˙500˙000.00

Map

 Project objective

Explanations are valuable because they scaffold the kind of learning that supports adaptive behaviour, e.g. explanations enable users to adapt themselves to the situations that are about to arise. Explanations allow us to attain a stable environment and have the possibility to control it, e.g. explanations put us in a better position to control the future. Explanations in the medical domain can help patients identify and monitor the abnormal behaviour of their ailment. In the domain of self-driving vehicles they can warn the user of some critical state and collaborate with her to prevent a wrong decision. In the domain of satellite imagery, an explanatory monitoring system justifying the evidence of a future hurricane can save millions of lives. Hence, a learning machine that a user can trust and easily operate need to be fashioned with the ability of explanation. Moreover, according to GDPR, an automatic decision maker is required to be transparent by law.

As decision makers, humans can justify their decisions with natural language and point to the evidence in the visual world which led to their decisions. In contrast, artificially intelligent systems are frequently seen as opaque and are unable to explain their decisions. This is particularly concerning as ultimately such systems fail in building trust with human users.

In this proposal, the goal is to build a fully transparent end-to-end trainable and explainable deep learning approach for visual scene understanding. To achieve this goal, we will make use of the positive interactions between multiple data modalities, incorporate uncertainty and temporal continuity constraints, as well as memory mechanisms. The output of this proposal will have direct consequences for many practical applications, most notably in mobile robotics and intelligent vehicles industry. This project will therefore strengthen the user’s trust in a very competitive market.

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The information about "DEXIM" are provided by the European Opendata Portal: CORDIS opendata.

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