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Augmented reality (AR) environments are suffering from a limited workspace. In addition, registration issues are also increased by the use of a mobile camera on the user that provides a first-person perspective (1PP). Using several fixed cameras reduces th ...
There has been increasing interest in the use of unsupervised adaptation for the personalisation of text-to-speech (TTS) voices, particularly in the context of speech-to-speech translation. This requires that we are able to generate adaptation transforms f ...
The purpose of this master project was to explore decision making process applied to a blackjack game and make the links with facets of impulsivity. The first part of this study goes through the mathematical of this game and presented the optimal policy, c ...
Uncertainties in design variables and problem parameters are often inevitable and must be considered in an optimization task if reliable optimal solutions are sought. Besides a number of sampling techniques, there exist several mathematical approximations ...
A possibility of estimating the finite-length performance of sparse-graph code ensembles gives two opportunities: to compare different codes of the same length in a context very close to real, practical applications and to perform the parameter optimizatio ...
There has been increasing interest in the use of unsupervised adaptation for the personalisation of text-to-speech (TTS) voices, particularly in the context of speech-to-speech translation. This requires that we are able to generate adaptation transforms f ...
Classifying materials from their appearance is challenging. Impressive results have been obtained under varying illumination and pose conditions. Still, the effect of scale variations and the possibility to generalise across different material samples are ...
Decision trees can be used to represent a large number of expert system rules in a compact way. We describe machine learning algorithms for learning decision trees. We have implemented the algorithms, including bagging and boosting techniques. We have depl ...
Statistical learning techniques have been used to dramatically speed-up keypoint matching by training a classifier to recognize a specific set of keypoints. However, the training itself is usually relatively slow and performed offline. Although methods hav ...
Seaport container terminals are source of many interesting large-scale optimization problems, which arise in the management of operations at several decision levels. In this paper we firstly illustrate a recently proposed framework, called two-stage column ...