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Publications associées (4)

AutoSynth: Learning to Generate 3D Training Data for Object Point Cloud Registration

Mathieu Salzmann, Zheng Dang

In the current deep learning paradigm, the amount and quality of training data are as critical as the network architecture and its training details. However, collecting, processing, and annotating real data at scale is difficult, expensive, and time-consum ...

Ieee Computer Soc2023

Hands-on tasks make learning visible: a learning analytics lens on the development of mechanistic problem-solving expertise in makerspaces

Richard Lee Davis, Bertrand Roland Schneider

This study investigated the impact of participating in a year-long digital-fabrication course on high-school seniors' problem-solving skills, with a focus on problems involving mechanistic systems. The research questions centered on whether working in a ma ...

Springer2023

Unsupervised classification of snowflake images using a generative adversarial network and K-medoids classification

Alexis Berne, Jussi Sakari Leinonen

The increasing availability of sensors imaging cloud and precipitation particles, like the Multi-Angle Snowflake Camera (MASC), has resulted in datasets comprising millions of images of falling snowflakes. Automated classification is required for effective ...

2020

The wheelchair as a full-body tool extending the peripersonal space

Olaf Blanke, Andrea Serino, Elisa Canzoneri

Dedicated multisensory mechanisms in the brain represent peripersonal space (PPS), a limited portion of space immediately surrounding the body. Previous studies have illustrated the malleability of PPS representation through hand-object interaction, showin ...

Frontiers Media2015