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The design of a self-improving tutor: PROTO-TEG

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What Face and Body Shapes Can Tell Us About Height

Pascal Fua, Helge Jochen Rhodin, Semih Günel

Recovering a person's height from a single image is important for virtual garment fitting, autonomous driving and surveillance. However, it is also very challenging without absolute scale information. Here, we examine the rarely addressed case, where camer ...

IEEE COMPUTER SOC2019

Machine Learning at the Atomic Scale

Michele Ceriotti, Félix Benedito Clément Musil

Statistical learning algorithms are finding more and more applications in science and technology. Atomic-scale modeling is no exception, with machine learning becoming commonplace as a tool to predict energy, forces and properties of molecules and condense ...

SWISS CHEMICAL SOC2019

Machine Learning at the Atomic Scale

Michele Ceriotti, Félix Benedito Clément Musil

2019

Combining UAV-imagery and machine learning for wildlife conservation

Semi-arid savannas are endangered by changes in the fragile equilibrium between rainfalls, fires and grazing pressure exerted by wildlife or cattle. To avoid bush encroachment and the decline of perennial grass, land managers must pay attention to keep the ...

2016

The Movement Error Rate for Evaluation of Machine Learning Methods for sEMG-based Hand Movement Classification

Barbara Caputo

There has been increasing interest in applying learning algorithms to improve the dexterity of myoelectric prostheses. In this work, we present a large-scale benchmark evaluation on the second iteration of the publicly released NinaPro database, which cont ...

2014

Open-Ended Learning of Visual and Multi-Modal Patterns

Jie Luo

A common trend in machine learning and pattern classification research is the exploitation of massive amounts of information in order to achieve an increase in performance. In particular, learning from huge collections of data obtained from the web, and us ...

EPFL2011

Open-ended Learning of Visual and Multi-modal Patterns

Jie Luo

Ecole polytechnique fédérale de Lausanne2011

Multiclass Transfer Learning from Unconstrained Priors

Barbara Caputo, Jie Luo, Tatiana Tommasi

The vast majority of transfer learning methods proposed in the visual recognition domain over the last years ad- dresses the problem of object category detection, assuming a strong control over the priors from which transfer is done. This is a strict condi ...

2011

Multiclass Transfer Learning from Unconstrained Priors

Barbara Caputo, Jie Luo, Tatiana Tommasi

Idiap2011

Learning and recovering 3D surface deformations

Mathieu Salzmann

Recovering the 3D deformations of a non-rigid surface from a single viewpoint has applications in many domains such as sports, entertainment, and medical imaging. Unfortunately, without any knowledge of the possible deformations that the object of interest ...

EPFL2009