Searched for: subject%3A%22deep%255C+learning%22
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Penning, Thijs (author)
Gaze estimation is an important area of research used in a wide range of applications. However, existing models trained for gaze estimation often suffer from high computational costs. In this study, frequency domain channel selection techniques were explored to decrease these costs by reducing the size of the input data. The main research...
bachelor thesis 2023
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Ossenkoppele, B.W. (author)
High-frame-rate volumetric ultrasound imaging is highly desired to enable novel clinical ultrasound applications. However, realizing high-quality volumetric ultrasound imaging at a high frame rates (>500 Hz) is challenging. Keeping the cable count and data rate of the transducer device at a realistic level without sacrificing image quality to...
doctoral thesis 2023
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Murgoci, Vlad (author)
This study investigates the relationship between deep learning models and the human brain, specifically focusing on the prediction of brain activity in response to static visual stimuli using functional magnetic resonance imaging (fMRI). By leveraging intermediate outputs of pre-trained convolutional neural networks (CNNs) with feature-weighted...
bachelor thesis 2023
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Kuiper, Thomas (author)
The amount of cars on the roads is increasing at a rapid pace, causing traffic jams to become commonplace. One way to decrease the amount of traffic congestion is by building an Intelligent Transportation System (ITS) which helps traffic flow optimally. An important tool for an ITS is short term traffic forecasting. Better forecasts will enable...
bachelor thesis 2023
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Sterrenberg, Amy (author)
Energy use, CO2 emissions, and waste production are all significant causes of environmental issues. The building sector is a major contributor to these problems, specifically the manufacturing of (structural) steel elements. Application of reuse and/or remanufacturing, as done in a circular economy, will reduce these effects. Therefore, these...
master thesis 2023
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Sassoon, Jordan (author)
Contrastive Language-Image Pretraining (CLIP) has gained vast interest due to its impressive performance on a variety of computer vision tasks: image classification, image retrieval, action recognition, feature extraction, and more. The model learns to associate images with their descriptions, a powerful method which allows it to perform well on...
bachelor thesis 2023
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El Coudi El Amrani, Nafie (author)
Neural Radiance Fields (NeRFs) have demonstrated remarkable capabilities in photo-realistic 3D reconstruction. NeRFs often take as input posed images where the camera poses come from either off-the-shelf S\textit{f}M or online optimization together with NeRFs. However, we find that both strategies yield suboptimal results in recovering camera...
master thesis 2023
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Pronk, Paco (author)
This study introduces a novel system that leverages three photodiodes and ambient light to identify air-written characters on a resource-constrained device. Through experimentation, suitable methods of data preprocessing, machine learning and model compression were selected to recognize the first 10 characters of the Latin alphabet. The final...
bachelor thesis 2023
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Beekhuizen, Michael (author)
Cardiovascular diseases are one of the primary causes of mortality worldwide. Paroxysmal atrial fibrillation is a specific type that is difficult to detect and diagnose in a short time frame. To overcome this, we investigated if long-term wearable data can be used for the detection of heart diseases. The BigIdeasLab_STEP dataset and long-term...
master thesis 2023
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Li, Xinqi (author)
Quantitative cardiac MRI is an increasingly important diagnostic tool for cardiovascular diseases. Yet, it is essential to have correct image registration for good accuracy and precision of quantitative mapping. Registering all baseline images from a quantitative cardiac MRI sequence, however, is nontrivial because the patient is moving, leading...
master thesis 2023
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van Loon, Joaquin (author)
Situational awareness within port areas is crucial to avoid collisions, navigate efficiently and reduce congestion. Maritime-traffic controllers constantly monitor the situation in the port and intervene when needed. This study proposes a deep learning model that predicts future vessel positions to assist in this process. The model employs a...
master thesis 2023
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Moes, Iris (author)
<b>Introduction: </b>Breast reconstruction after a mastectomy is crucial to improve a patient’s quality of life. The Deep Inferior Epigastric artery Perforator (DIEP) flap procedure is considered the golden standard for breast reconstruction. Three-dimensional (3D) visualization methods have shown promise in providing a better understanding of...
master thesis 2023
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Keurhorst, Adriaan (author)
The Alps are experiencing a gradual reduction in snow cover due to rising temperatures, impacting the landscape and dependent ecosystems. While several models have been developed to study snow cover in the region, there is a lack of visual representations. This research employs a Conditional Generative Adversarial Network (cGAN) to generate a...
master thesis 2023
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Martens, Bruno (author)
Critical to the safe application of autonomous vehicles is the ability to accurately predict the future motion of agents surrounding the vehicle. This is especially important - and challenging - in urban traffic, where vehicles share the road with Vulnerable Road Users (VRUs) such as pedestrians and cyclists. However, the majority of the...
master thesis 2023
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Hoendermis, Dora (author)
Radiotherapy is one of the main treatments for cancer and relies heavily on CT images to calculate radiation dose. With research on radiotherapy moving to adaptive treatments aiming to calculate these doses at real-time speeds while maintaining high precision, a need for accurate CT imaging at comparable real-time speeds has emerged. Currently,...
master thesis 2023
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Blom, Joris (author)
Fog plays a major role in chain collisions. Proper fog detection is essential for the Dutch road authority to anticipate foggy weather conditions. Dozens of stations in the Netherlands can measure fog. However, fog can be a very local phenomenon. Therefore, more local measurements are needed. There are about 5,000 traffic cameras in...
master thesis 2023
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Schuurman, Kevin (author)
The use of deep learning in global weather forecasting has shown significant promise in improving both forecasting accuracy and speed. Traditional numerical weather prediction models have gradually improved forecasting skills but at the cost of increased computational complexity. In contrast, new deep learning models, trained directly on...
master thesis 2023
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Galjaard, Jeroen (author)
Few-shot learning presents the challenging problem of learning a task with only a few provided examples. Gradient-Based Meta-Learners (GBML) offer a solution for learning such few-shot problems. These learners approach the few-shot problem by learning an initial parameterization that requires only a few adaptation steps for new tasks. Although...
master thesis 2023
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Geel, Patrick (author)
The demand for implementing neural networks on edge devices has rapidly increased as they allow designers to move away from expensive server-grade hardware. However, due to the limited resources available on edge devices, it is challenging to implement complex neural networks. This study selected the Kria SoM KV260 hardware platform due to its...
master thesis 2023
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Pastor Serrano, O. (author)
doctoral thesis 2023
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