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Chen, Shaoqing (author)
Environmental sound identification and recognition aim to detect sound events within an audio clip. This technology is useful in many real-world applications such as security systems, smart vehicle navigation and surveillance of noise pollution, etc. Research on this topic has received increased attention in recent years. Performance is...
master thesis 2020
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de Jong, Richard (author)
Persistent surveillance is an urgent proficiency. For security, surveillance cameras are a strong asset as they support the automatic tracking of people and are directly interpretable by a human operator. Radar on the other hand can be used under a broad range of circumstances: radar can penetrate mediums such as clouds, fogs, mist and snow, and...
master thesis 2019
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Batheja, Dhruv (author)
This work tackles the problem of repetition counting in videos using modern deep learning techniques. For this task, the intention is to build an end-to-end trainable model that could estimate the number of repetitions without having to manually intervene with the feature selection process. The models that exist currently perform well on videos...
master thesis 2019
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Bekendam, Matthijs (author)
The Delft Center for Systems and Control (DCSC) 'Smart Optics' aim to achieve higher resolution imaging through Adaptive Optics (AO). Adaptive optics is a modern technique for detecting and correcting real-time wavefront aberrations and is widely used in biomedical imaging and astronomical imaging. Wavefront sensing lies at the core of Adaptive...
master thesis 2020
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Garbacz, Mateusz (author)
Being capable to foresee the future of a given financial asset as an investor, may lead to significant economic profits. Therefore, stock market prediction is a field that has been extensively developed by numerous researchers and companies. Recently, however, a new branch of financial assets has emerged, namely cryptocurrencies. As a...
master thesis 2018
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Werner, Oliver (author)
In clinical practice, as a first approximation, the severity of an abnormality on an image is often determined by measuring its volume. Researchers often first segment this abnormality with a neural network trained by voxel-wise labels and thereafter extract the volume. Instead of this indirect two steps approach, we propose to train neural...
master thesis 2020
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Choi, Yapkan (author)
Person re-identification based on appearance is challenging due to varying views and lighting conditions in different cameras, or when multiple persons wear similar clothing styles and color. Considering these challenges, gait patterns provide an alternative to appearance, as gait can be captured from a distance and at a low resolution. In this...
master thesis 2020
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Sadon, A.P.J. (author)
Het onderzoek heeft zich gericht op de ontwikkeling van een Semantisch Connectionistisch Redeneersysteem (SCORE). SCORE kan de basis vormen voor een volwaardig expertsysteem. De, voor een expertsysteem van elementair belang zijnde, fundamentele inferentie principes, kennisacquisitie principes en kennisrepresentatievormen hebben in SCORE de...
master thesis 1990
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Suryamurthy, Vivekanandan (author)
Intelligent terrain perception for search-and-rescue robotic applications, requires a high-level understanding of both the terrain type and its chief physical characteristics. Roughness is one such important terrain property, since it could play a key role in robot control/planning strategies, while navigating<br/>in an unknown environment. In...
master thesis 2018
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van Hilten, Arno (author)
Cardiovascular diseases and stroke are currently the leading causes of death worldwide. Atherosclerotic plaque is a mostly asymptotic vascular disease, but rupture of an atherosclerotic plaque in the carotid artery could lead to stroke. Automated segmentation of plaque components could help improve risk assessment by producing fast and reliable...
master thesis 2018
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Soilis, P. (author)
Deep learning models have achieved state-of-the-art performance on several image classification tasks over the past years. Several studies claim to approach or even surpass human-levels of performance when using such models to classify images. However, these architectures are notoriously complex, thus making their interpretation a challenge....
master thesis 2020
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García Sanz, María (author)
Patients with 1p/19q co-deleted low grade glioma (LGGs) have better prognosis and react better to certain treatments than patients with intact 1p/19q LGG. Currently, information about the 1p/19q co-deletion status is obtained by means of an invasive procedure called biopsy. As an alternative, non-invasive techniques to extract this information...
master thesis 2019
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Knyazev, Norman (author)
Many widely used Recommender System algorithms estimate user tastes without accounting for their evolving nature. In recent years there has been a gradual increase in methods incorporating such temporal dynamics through sequential processing of user consumption histories. Some works have also included additional temporal features such as time...
master thesis 2020
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Bonhof, Stefan (author)
Performing tasks in dynamic environments is still an open challenge in robotics. To be able to perform a task reliably in such scenarios, the state of the world has to be continuously monitored. In this context, most state-of-the-art perception methods focus on the recognition and classification of individual objects. However, these methods...
master thesis 2020
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Kapadia, Husain (author)
Listening in noise is a challenging problem that affects the hearing capability of not only normal hearing but especially hearing impaired people. Since the last four decades, enhancing the quality and intelligibility of noise corrupted speech by reducing the effect of noise has been addressed using statistical signal processing techniques as...
master thesis 2019
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Mus, D.A. (author)
In order to interact with environments and appliances made for humans, robots should be able to manipulate a large variety of objects and appliances in human environments. When having experience with manipulating a certain object or appliance, a robot should be able to generalize this behaviour to novel, but similar objects and appliances. When...
master thesis 2017
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Fris, Rein (author)
Deep Reinforcement Learning (DRL) enables us to design controllers for complex tasks with a deep learning approach. It allows us to design controllers that are otherwise cumbersome to design with conventional control methodologies. Often, an objective for RL is binary in nature. However, exploring in environments with sparse rewards is a problem...
master thesis 2020
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Friđriksdóttir, Esther (author)
Physical activity and mobility are important indicators of the recovery process of patients in the general ward of the hospital. Currently, monitoring mobility of hospitalized patients relies largely on direct observation from the caregivers. Accelerometers have the potential to quantify physical activity of patients objectively and without...
master thesis 2019
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Samiotis, Ioannis Petros (author)
Side-Channel Attacks, are a prominent type of attacks, used to break cryptographic implementations on a computing system. They are based on information "leaked" by the hardware of a computing system, rather than the encryption algorithm itself. Recent studies showed that Side-Channel Attacks can be performed using Deep Learning models. In this...
master thesis 2018
document
Jacquemod, Laura (author)
master thesis 2017
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