Articles

//Articles

Flemish AI initiatives

2018-11-13T09:02:07+00:00November 13th, 2018|Articles|

In recent months, the department for Economy, Science and Innovation of the Flemish government has taken a number of initiatives concerning AI. In July, they organised a Stakeholders' day on Artificiële Intelligence to bring together practitioners, researchers and other interested parties, in an effort to map the Flemish AI landscape and identify key concerns going forward. From [...]

Dutch AI Manifesto

2018-10-12T10:06:03+00:00September 27th, 2018|Articles|

Since 2017, BNVKI collaborates with the Netherlands Platform for ICT Research (http://www.ictonderzoek.net/). On the initiative of the BNVKI board, a Special Interest Group on AI has been created, consisting of researchers from each of the 12 IPN institutes, which are representative for the AI community in the Netherlands. Having the status of a special member [...]

Virginia Dignum Elected EurAI Fellow

2018-07-20T09:28:19+00:00July 20th, 2018|Articles|

Virginia Dignum has recently been elected as Fellow of the European Artificial Intelligence Association (EURAI). The EURAI Fellows programme recognises European AI researchers who have made exceptional contributions to the field. The Fellows are selected from the top 3% AI researchers in Europe. In recent years, Virginia has played an important role in putting responsible [...]

CLAIRE – Confederation of Laboratories for Artificial Intelligence in Europe

2018-06-25T10:08:06+00:00June 25th, 2018|Articles|

The CLAIRE initiative, initiated by Holger Hoos, Morten Irgens, and Philipp Slusallek, is aimed at uniting the AI community in Europe and guiding EU and national administrations in allocating funding for excellence in AI research. In a nutshell, CLAIRE is about “Excellence across all of AI. For all of Europe. With a Human-Centred Focus.” Everyone [...]

BNAIC 2017 Postproceedings Published

2018-05-16T09:06:46+00:00May 7th, 2018|Articles|

The BNAIC 2017 postproceedings were published in the Springer CCIS series. It contains all 11 Type A regular papers accepted for oral presentation (37% of the 30 Type A submissions). Verheij, B., & Wiering, M. (eds.) (2018). Artificial Intelligence. 29th Benelux Conference, BNAIC 2017. Groningen, The Netherlands, November 8-9, 2017. Revised Selected Papers (Communications in Computer and [...]

EU Communication on AI

2018-05-07T09:26:55+00:00May 7th, 2018|Articles|

On April 25th, 2018, the European Commission has published a Communication outlining a European approach to AI, based on three pillars: Boosting the EU's technological and industrial capacity and AI uptake across the economy, both by the private and public sectors. This includes investments in research and innovation and better access to data. Preparing for socio-economic [...]

Changes to the BNVKI board

2018-02-02T18:17:09+00:00February 2nd, 2018|Articles|

As per January 2018, BNVKI has a new board. Koen Hindriks and Marc van Zee have left the board, and are thanked for their excellent contribution over the past years. They have been replaced by Mike Ligthart (TU Delft) and Yingqian Zhang (TU Eindhoven). Mike will take the role of editor of the newsletter, and [...]

The VIPER project: Visual Person Detection Made Reliable

2017-10-19T12:57:35+00:00September 28th, 2017|Announcements, Articles|

The VIPER project was a two-year Technology Transfer project, sponsored by Flanders Innovation & Entrepreneurship, and conducted by the research group EAVISE of KU Leuven, Campus De Nayer, in collaboration with a consortium of a dozen different companies. The goal of this project was to study reliable methods of detecting people in camera footage for [...]

What’s Hot: Machine Learning for the Quantified Self

2017-10-19T12:58:45+00:00September 25th, 2017|Articles|

Abstract Nowadays, an ever increasing number of sensors surround us that collect information about our behavior and activities. Devices that embed these sensors include smartphones, smartwatches, and other types of personal devices we wear or carry with us. Machine learning techniques are an obvious choice to identifying useful patterns from this rich source of data. [...]