Cooperative camera scene modeling using metadata.

01 October 2021 → 30 September 2022
Regional and community funding: Special Research Fund
Research disciplines
  • Natural sciences
    • Visual data analysis
  • Engineering and technology
    • Computer vision
    • Pattern recognition and neural networks
embedded vision systems vision processing chips smart image sensors distributed vision systems cooperative vision smart traffic human behaviour modelling machine learning deep learning
Project description

ACHIEVE-ETN aims at training a new generation of scientists through a research programme on highly integrated hardwaresoftware components for the implementation of ultra-efficient embedded vision systems as the basis for innovative distributed vision applications. They will develop core skills in multiple disciplines, from image sensor design to distributed vision algorithms, and at the same time they will share the multidisciplinary background that is necessary to understand complex problems in information-intensive vision-enabled applications. Concurrently, they will develop a set of transferable skills to promote their ability to cast their research results into new products and services, as well as to boost their career perspectives overall. Altogether, ACHIEVE-ETN will prepare highly skilled early-stage researchers able to create innovative solutions for emerging technology markets in Europe and worldwide but also to drive new businesses through engaging in related entrepreneurial activities. The consortium is composed of 6 academic and 1 industrial beneficiaries and 4 industrial partners. The training of the 9 ESR’s will be achieved by the proper combination of excellent research, secondments with industry, specific courses on core and transferable skills, and academic-industrial workshops and networking events, all in compliance with the call’s objectives of international, intersectoral and interdisciplinary mobility.