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Active learning for monitoring network optimization

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Many amputees have maps of referred sensation from their missing hand on their residual limb (phantom maps). This skin area can serve as a target for providing amputees with tactile sensory feedback. Providing tactile feedback on the phantom map can improv ...

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Introducing Geometry in Active Learning for Image Segmentation

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We propose an Active Learning approach to training a segmentation classifier that exploits geometric priors to streamline the annotation process in 3D image volumes. To this end, we use these priors not only to select voxels most in need of annotation but ...

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Transfer Learning through Greedy Subset Selection

Barbara Caputo, Ilja Kuzborskij

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Idiap2015

SVM Active Learning Approach for Image Classification Using Spatial Information

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In the last few years, active learning has been gaining growing interest in the remote sensing community in optimizing the process of training sample collection for supervised image classification. Current strategies formulate the active learning problem i ...

Ieee-Inst Electrical Electronics Engineers Inc2014

Towards teacher-led design inquiry of learning

Maria Jesus Rodriguez Triana

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Active Learning: Any Value for Classification of Remotely Sensed Data?

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Active learning, which has a strong impact on processing data prior to the classification phase, is an active research area within the machine learning community, and is now being extended for remote sensing applications. To be effective, classification mu ...

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Learning User's Confidence for Active Learning

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Ieee-Inst Electrical Electronics Engineers Inc2013

Active Learning of Multi-Index Function Models

Volkan Cevher, Hemant Tyagi

We consider the problem of actively learning \textit{multi-index} functions of the form

f(x) = g(Ax)= \sum_{i=1}^k g_i(a_i^Tx)

from point evaluations of

f

. We assume that the function

f

is defined on an

\ell_2

-ball in

\Real^d

g

is twice contin ...

2012

Using active learning for monitoring networks design: the example of wind power plants sites evaluation

Devis Tuia, Alexei Pozdnoukhov

Locating new wind farms is of crucial importance for energy policies of the next decade. To select the new location, an accurate picture of the wind fields is necessary. However, characterizing wind fields is a difficult task, since the phenomenon is highl ...

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Discovering single classes in remote sensing images with active learning

Devis Tuia

When dealing with supervised target detection, the acquisition of labeled samples is one of the most critical phases: the samples must be yet representative of the class of interest, but must also be found among a vast majority of non-target examples. More ...

2012

Active Learning of Multi-Index Function Models

Volkan Cevher, Hemant Tyagi

We consider the problem of actively learning \textit{multi-index} functions of the form

f(x) = g(Ax)= \sum_{i=1}^k g_i(a_i^Tx)

from point evaluations of

f

. We assume that the function

f

is defined on an

\ell_2

-ball in

\Real^d

g

is twice contin ...

2012