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Tatiana Tommasi

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Publications associées (19)

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A Deeper Look at Dataset Bias

Barbara Caputo, Tatiana Tommasi, Novi Patricia

The presence of a bias in each image data collection has recently attracted a lot of attention in the computer vision community showing the limits in generalization of any learning method trained on a specific dataset. At the same time, with the rapid deve ...

Springer Int Publishing Ag2015

Learning Categories from Few Examples with Multi Model Knowledge Transfer

Barbara Caputo, Tatiana Tommasi

Learning a visual object category from few samples is a compelling and challenging problem. In several real-world applications collecting many annotated data is costly and not always possible. However a small training set does not allow to cover the high i ...

Idiap2013

Improving Control of Dexterous Hand Prostheses Using Adaptive Learning

Barbara Caputo, Tatiana Tommasi

At the time of this writing, the main means of control for polyarticulated self-powered hand prostheses is surface electromyography (sEMG). In the clinical setting, data collected from two electrodes are used to guide the hand movements selecting among a f ...

Ieee-Inst Electrical Electronics Engineers Inc2013

Leveraging over prior knowledge for online learning of visual categories

Barbara Caputo, Tatiana Tommasi, Mohsen Kaboli

Open ended learning is a dynamic process based on the continuous analysis of new data, guided by past experience. On one side it is helpful to take advantage of prior knowledge when only few information on a new task is available (transfer learning). On th ...

2012

While there is a general consensus that autonomous robots should be able to learn continuously over time, the learning process is traditionally envisioned for each specific robot situated in a given environment. This does not consider the fact that robots ...

Idiap2012

At the time of writing, highly dexterous hand prostheses are being manufactured and, to some extent, marketed. This means wearable, implantable mechanical hands with many independently controllable degrees of freedom, e.g. finger flexion and thumb rotation ...

Idiap2012

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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

The more you know, the less you learn: from knowledge transfer to one-shot learning of object categories

Barbara Caputo, Tatiana Tommasi

Learning a category from few examples is a challenging task for vision algorithms, while psychological studies have shown that humans are able to generalise correctly even from a single instance (one-shot learning). The most accredited hypothesis is that h ...

2009

Discriminative cue integration for medical image annotation

Barbara Caputo, Tatiana Tommasi

Automatic annotation of medical images is an increasingly important tool for physicians in their daily activity. Hospitals nowadays produce an increasing amount of data. Manual annotation is very costly and prone to human mistakes. This paper proposes a mu ...

2008