Idiap and the 3D2cut company developed a system capable of identifying vines and of assisting pruning. A scientific publication resulted from this collaboration. This project was supported by the The Ark foundation for innovation in Valais.
An Innosuisse project allowed Idiap to set up AI tools able to help experts to study the manufacturability of new aluminum elements requested by their customers.
Idiap Research Institute and the School of Engineering at EPFL invite applications for the directorship of Idiap. The successful candidate will also hold a faculty position as full professor at EPFL School of Engineering.
Suraj Srinivas and Weipeng He received the 2021 PhD Thesis Distinction in Electrical Engineering by the EPFL.
Artificial intelligence and big data pioneers Octopeek (France) and Idiap announce a partnership. A member of Octopeek’s scientific staff will spend four years at the very heart of Idiap, culminating in a PhD—a unique opportunity to use video data to develop research on multimodal learning, and to spur innovation.
Human-robot interactions are often lacking fluidity, especially outside of the lab. Today, researchers from Idiap are publishing in open access the algorithms which allowed a robot to be used in real conditions in a shopping mall in Finland in the framework of the European project Mummer.
The Perception and Activity Understanding group presents the unified system of visual, audio, and non-verbal perception that is currently used within the MuMMER.
The Perception and Activity Understanding group attended the IEEE International Conference on Intelligent Robots and Systems (IROS), in Madrid.
The paper "Deep Neural Networks for Multiple Speaker Detection and Localization" by Weipeng He, Petr Motlicek and Jean-Marc Odobez shows that the deep learning-based method achieves 90% precision and recall for localizing multiple speakers in real robot recordings.
This thesis presents visual analysis methods for complex ancient Maya writings, specifically a promising crowdsourcing approach to build a large glyph dataset, competitive data-driven visual representations, and interpretable visualization methods that can be applied to explore various other Digital Humanities datasets.
The Eumssi team led by Idiap and comprising as well the LIUM partner ranked first out of 6 teams in the Person Discovery challenge of the MediaEval benchmarking initiative.
Enhanced vine pruning thanks to artificial intelligence and augmented reality
