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Sorgedrager, Riemer (author)
This study focuses on automated malaria diagnosis in low quality blood smear images, captured by a low-cost smartphone based microscope system. The aim is to localize and classify the healthy and infected erythrocytes (red blood cells) in order to evaluate the parasitaemia in an infected blood smear. Due to the lower quality of the smartphone...
master thesis 2018
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Xie, Yu (author)
Facing the severe air pollution phenomenon in urban areas and the subsequent low visibility event in airports, it is urgent to conduct air quality and visibility predictions to better reflect their changing trends. However, the variations of PM2.5 and visibility involve complicated physical and chemical processes, which make their accurate...
master thesis 2018
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Dijkstra, Timo Johannes (author)
The versatility of the hands is revealed in its movements, but often not noticed before trauma occurs. Joint range of motion is used as a measure to follow the progress of diseases. A digital workflow for 3D data in medical appliances is envisioned for years.<br/>The aim of this research is to develop a method that reliably and reproducability...
master thesis 2018
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van Wijnen, Kimberlin (author)
Perivascular spaces (PVS) visible on MRI are currently emerging as an important potential neuroimaging marker for several pathologies in the brain like Alzheimer’s disease and cerebral small vessel disease. PVS are fluid-filled spaces surrounding vessels as they enter the brain. Although PVS are normally not noticeable on MRI scans acquired at...
master thesis 2018
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Brand, Patrick (author)
Recent advances in Artificial Intelligence and Computer Vision have been showed to be promising for automated land use classification of remotely sensed data. However, current state-of-the-art per-pixel segmentation networks fail to accurately capture geometrical and topological properties on land use segmentation, as these methods have...
master thesis 2019
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Resink, Tim (author)
To be able to understand the dynamic driving environment, an autonomous vehicle needs to predict the mo- tion of other traffic participants in the driving scene. Motion prediction can be done based on experience and recently observed series of past events, and entails reasoning about probable outcomes with these past ob- servations. Aspects that...
master thesis 2019
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Al-Rahbi, Mohammed (author)
Human Activity Recognition (HAR) is a key enabler of various applications, including smart homes, health care, Internet of Things (IoT), and virtual reality games. A large number of HAR systems are based on wearable sensors and computer vision. However, a challenge that has emerged in the last few years entails recognizing human activities using...
master thesis 2019
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Li, Mingxi (author)
Neural networks have achieved great success in many difficult learning tasks like image classification, speech recognition and natural language processing. However, neural architectures are hard to design, which requires lots of knowledge and time of human experts. Therefore, there has been a growing interest in automating the process of designing...
master thesis 2019
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van der Valk, Daan (author)
Side-channel attacks (SCA) aim to extract a secret cryptographic key from a device, based on unintended leakage. Profiled attacks are the most powerful SCAs, as they assume the attacker has a perfect copy of the target device under his control. In recent years, machine learning (ML) and deep learning (DL) techniques have became popular as...
master thesis 2019
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Dong, Jiaao (author)
In order to achieve redundancy and improve the robustness of an autonomous driving system, radar is a suitable choice for road user detection task in severe working conditions (e.g. darkness, bad weather). However, the real-time multi-class radar based road user detection algorithm is less explored compared with camera and LiDAR solutions. To...
master thesis 2019
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Papanastasiou, Vasileios (author)
The radar micro-Doppler (m-D) signature of human gait has already been used successfully for a few classification tasks of human gait, for instance walking versus running and determining the number of humans under observation. owever, the more challenging problem of personnel identification has not been solved yet. The aim of this study is to...
master thesis 2019
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Papadakis, Manolis (author)
Biometrics authentication has been very useful and necessary nowadays due to the great developments in technology and the transaction of huge amounts of sensitive data on a daily basis. Traditionally, access to some data or service is achieved by means of some documents or a password. However, these methods are not very convenient. Alternatively...
master thesis 2019
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Wiersma, Ruben (author)
We present a new approach for deep learning on surfaces, combining geometric convolutional networks with rotationally equivariant networks. Existing work either learns rotationally invariant filters, or learns filters in the tangent plane without correctly relating orientations between different tangent planes (orientation ambiguity). We propose...
master thesis 2019
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Ji, Chenhong (author)
Image registration is a vital tool in medical image analysis with a large number of applications assisting the medical experts. Currently, conventional image registration approach with predefined dissimilarity metric and iterative optimization, is widely used. In this thesis, we proposed a method to solve medical image registration problem using...
master thesis 2019
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Klaassen, Pim (author)
The contemporary trend shows a shift from rule-based algorithms to deep learning. In the last few years, this field has been developing rapidly and its popularity has increased to a large extent. This happened for a good reason, since deep learning was able to solve some of the hardest problems in fields like image recognition, natural language...
master thesis 2019
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Khan, Tiamur (author)
Visual surveillance technologies are increasingly being used to monitor public spaces. These technologies process the recordings of surveillance cameras. Such recordings contain depictions of human actions such as "running", "waving", and "aggression". In the field of computer vision, automated detection of human actions in videos is known as...
master thesis 2019
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Meij, Senna (author)
The operating room is one of the most complex and expensive environments in the hospital. Research has been focusing on improving the efficient use of the OR time, for instance by using intraoperative data to update the planning of the OR during the day. This thesis used a deep learning network to automatically recognize surgical tools and pre...
master thesis 2019
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Enthoven, David (author)
With the increasing number of data collectors such as smartphones, immense amounts of data are available. These data have great value for training machine learning models. Federated learning is a distributed machine learning approach that allows a machine learning model to train on a distributed data-set without transferring any data and...
master thesis 2019
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Sharma, Saurabh (author)
Pavement undergoes a fast deterioration process either due to the damages induced by weather conditions, an increase in traffic flow and load, or passive factors like aging of infrastructure. Thus requiring periodic rehabilitation measures to maintain the condition of the underlying asset. Since damages on the asphalt road, impose economic...
master thesis 2020
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Gupta, Sukrit (author)
A lot research has been conducted in the field of autonomous navigation of mobile robots with focus on Robot Vision and Robot Motion Planning. However, most of the classical navigation solutions require several steps of data pre-processing and hand tuning of parameters, with separate modules for vision, localization, planning and control. All...
master thesis 2020
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