A Deep Learning approach for boulder detection –The key to understand planetary surfaces evolution and their crater statistics-based ages

Project description

Boulder mapping could help reveal how planetary surfaces evolved

Fields of science

• natural sciences › physical sciences › astronomy › planetary sciences › planetary geology
• engineering and technology › environmental engineering › remote sensing
• natural sciences › physical sciences › astronomy › planetary sciences › natural satellites
• natural sciences › computer and information sciences › artificial intelligence › machine learning › deep learning
• natural sciences › computer and information sciences › artificial intelligence › computational intelligence

Programme(s)

• H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions Main Programme
• H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility

Topic(s)

• MSCA-IF-2020 - Individual Fellowships

Call for proposal

H2020-MSCA-IF-2020

See other projects for this call

Funding Scheme

MSCA-IF-GF - Global Fellowships

Coordinator

UNIVERSITETET I OSLO

Net EU contribution

€ 284 345,28

Address

Problemveien 5-7
0313 Oslo
Norway

Region

Norge › Oslo og Viken › Oslo

Activity type

Higher or Secondary Education Establishments

Links

Other funding

€ 0,00

Partners (1)

Partner

Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.

BOARD OF TRUSTEES OF THE LELAND STANFORD JUNIOR UNIVERSITY

United States

Net EU contribution

€ 0,00

Address

Serra Mall 450
94305 2004 Stanford

Activity type

Higher or Secondary Education Establishments

Links

Other funding

€ 177 265,92