Parametrized classifiers for optimal EFT sensitivity
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We describe and analyze a discriminative algorithm for learning to align a phoneme sequence of a speech utterance with its acoustical signal counterpart by predicting a timing sequence representing the phoneme start times. In contrast to common HMM-based a ...
Multiple kernel learning (MKL) aims at simultaneously learning a kernel and the associated predictor in supervised learning settings. For the support vector machine, an efficient and general multiple kernel learning algorithm, based on semi-infinite linear ...
This paper introduces a discriminative model for the retrieval of images from text queries. Our approach formalizes the retrieval task as a ranking problem, and introduces a learning procedure optimizing a criterion related to the ranking performance. The ...
The main challenge of new information technologies is to retrieve intelligible information from the large volume of digital data gathered every day. Among the variety of existing data sources, the satellites continuously observing the surface of the Earth ...
EPFL2014
Biometric authentication can be cast as a signal processing and statistical pattern recognition problem. As such, it relies on models of signal representations that can be used to discriminate between classes. One of the assumptions typically made by the p ...
EPFL2008
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
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A crucial feature of a good scene recognition algorithm is its ability to generalize. Scene categories, especially those related to human made indoor places or to human activities like sports, do present a high degree of intra-class variability, which in t ...
2014
In this work a new method for automatic image classification is proposed. It relies on a compact representation of images using sets of sparse binary features. This work first evaluates the Fast Retina Keypoint binary descriptor and proposes imp ...
Detection of elongated structures in 2D images and 3D image stacks is a critical prerequisite in many applications and Machine Learning-based approaches have recently been shown to deliver superior performance. However, these methods essentially classify i ...
Segmenting images is a significant challenge that has drawn a lot of attention from different fields of artificial intelligence and has many practical applications. One such challenge addressed in this thesis is the segmentation of electron microscope (EM) ...
