Searched for: contributor:"Loog, M. (mentor)"
(1 - 14 of 14)
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Boon, K. (author)
In this thesis I develop a Machine Learning method to combine galactic redshift estimates of previous authors into an aggregate estimate. I investigate weather combining earlier results into a single estimate is a worthwhile effort. Disagreement between the earlier results is used as a metric the quality of estimation. This disagreement is...
master thesis 2017
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Luktuke, Y.Y. (author)
master thesis 2017
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Pals, T.E. (author)
This paper evaluates a method that improves segmentation e ciency by intelligently suggesting planes where correction is most valuable. An existing method is extended to work for segmentation of multiple bones simultaneously. This method is evaluated because in clinical practice it is often necessary that scans are segmented very accurate. When...
master thesis 2017
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Sloots, J.J. (author)
Machine learning approaches are increasingly successful in medical image analysis. Still, learning from MR images poses some serious challenges. Scanner-dependent characteristics effect feature representations directly and hamper the clinical implementation of otherwise successful supervised-learning techniques. To compensate for variations in...
master thesis 2016
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van Rosmalen, N.C. (author)
To possess a computer algorithm that can perform the popular task of object localization with only weak supervision is valuable for numerous reasons. Often enough a certain localization task (e.g. bird localization) simply does not have properly annotated training data available. In this thesis a novel approach called Positive Class Localization...
master thesis 2016
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Viering, T.J. (author)
In many settings in practice it is expensive to obtain labeled data while unlabeled data is abundant. This is problematic if one wants to train accurate (supervised) predictive models. The main idea behind active learning is that models can perform better with less labeled data, if the model may choose the data from which it learns. Active...
master thesis 2016
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Van der Laan, T.A. (author)
The works [Volodymyr et al. Playing atari with deep reinforcement learning. arXiv preprint arXiv:1312.5602, 2013.] and [Volodymyr et al. Human-level control through deep reinforcement learning. Nature, 518(7540):529–533, 2015.] have demonstrated the power of combining deep neural networks with Watkins Q learning. They introduce deep Q networks ...
master thesis 2015
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Runia, T.F.H. (author)
In this thesis we design, implement and study a high-speed object detection framework. Our baseline detector uses integral channel features as object representation and AdaBoost as supervised learning algorithm. We suggest the implementation of two approximation techniques for speeding up the baseline detector and show their effectiveness by...
master thesis 2015
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Van Tulder, G. (author)
Recent advances in importance-weighted active learning solve many of the problems of traditional active learning strategies. But does importance-weighted active learning also produce a reusable sample selection? This thesis explains why reusability can be a problem, how importance-weighted active learning removes some of the barriers to...
master thesis 2012
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Krijthe, J.H. (author)
In order to choose from the large number of classification methods available for use, cross-validation error estimates are often employed. We present this cross-validation selection strategy in the framework of meta-learning and show that conceptually, meta-learning techniques could provide better classifier selections than traditional cross...
master thesis 2012
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Smeelen, M.A. (author)
Nowadays, for the defense and security community, it is of prior importance to classify threats that are merged in a background while at the same time understanding the context of the entire scene. Traditional TV and Infra-Red (IR) cameras allow for an easy context understanding by providing valuable background and scenery information....
master thesis 2012
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Van Giessen, A. (author)
Alzheimer's disease (AD) is a type of dementia which is difficult to diagnose based on clinical observations. Many automated classification algorithms are being developed to aid in the diagnosis. In such algorithms, principal components analysis (PCA) is a popular tool to reduce the dimension of data, get rid of noise and redundancy and thereby...
master thesis 2012
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Van de Sande, J.J.M. (author)
Undesired, human behavior in public environments is an increasing issue in today’s society. The overload of security operators and law enforcement addresses the need for automatic detection of anomalous behavior. The EU-project ADABTS aims to facilitate the protection of EU citizens, property and infrastructure against threats of terrorism,...
master thesis 2012
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Loni, B. (author)
An important component of question answering systems is question classification. The task of question classification is to predict the entity type of the answer of a natural language question. Question classification is typically done using machine learning techniques. Different lexical, syntactical and semantic features can be extracted from a...
master thesis 2011
Searched for: contributor:"Loog, M. (mentor)"
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