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- van den Bent, Luuk (author) master thesis 2023
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Borren, Noor (author)Introduction: Trauma-induced rib fractures are a common injury, affecting millions of individuals globally each year. Although anteroposterior thoracic radiographs are part of the standard posttraumatic screening, the most sensitive modality, and therefore golden standard for diagnosing rib fractures, is computed tomography (CT). Still, between...master thesis 2023
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Haarman, Luuk (author)Convolutional Neural Networks (CNNs) benefit from fine-grained details in high-resolution images, but these images are not always easily available as data collection can be expensive or time-consuming. Transfer learning pre-trains models on data from a related domain before fine-tuning on the main domain, and is a common strategy to deal with...master thesis 2023
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Six, Kobi (author)The aviation industry's reliance on automation raises concerns about pilot complacency, necessitating continuous pilot proficiency measures. To that end, real-time pilot skill feedback is vital—through alerts on declining skill levels or scalable levels of autonomy. Current cybernetic methods are limited as they assume linearity and time...master thesis 2023
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Polak, Max (author)Incipient slip detection plays an important role in human and robotic grasping. With the growing use of deep learning in vision-based tactile sensing, the black-box nature of these deep neural networks (DNNs) makes it difficult to analyze, debug, and validate their behavior and learned patterns. To fill this gap, eXplainable AI (XAI) methods...master thesis 2023
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Sharma, Anirvin (author)Image data augmentation has been regarded as a reliable and effective way to increase the data available for training. With the advent and rise of Generative AI, generative data augmentation has been shown to realize even better gains in performance for downstream tasks. However, these performance gains are often the cause of "extra information"...master thesis 2023
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Mukherjee, Sayak (author)Current methods in Federated and Decentralized learning presume that all clients share the same model architecture, assuming model homogeneity. However, in practice, this assumption may not always hold due to hardware differences. While prior research has addressed model heterogeneity in Federated Learning, it remains unexplored in fully...master thesis 2023
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Yao, Zhongbo (author)This thesis aims at maximizing the profit of a strawberry producer while satisfying the retailer's demand and meeting other constraints. The amount of strawberries to be delivered to the retailer signed in the contract is the main decision variable to be optimized in the problem. Furthermore, the transportation scheduling is also optimized to...master thesis 2023
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Pappas, Apostolos (author)<br/>master thesis 2023
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Kyriazis, Ioannis (author)Patients with neuromuscular diseases that are unable to speak, but whose cognitive ability has been maintained, can be benefited from Brain Computer Interfaces (BCIs). The decoding of inner (covert) speech from EEGs consists of one of the state of the art methods that aim to tackle this issue. High variability between subjects, as well as low...master thesis 2023
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WANG, HAORAN (author)In contrast to the prevalent focus on real photos in computer vision research, we present a contribution by making the Ot & Sien dataset machine learning-ready for object detection tasks in illustrations. We refer to the new dataset as Ot & Sien++ that is composed of scanned images of children’s book illustrations, thereby venturing into...master thesis 2023
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van Amerongen, Maximilian (author)Artificial Neural Networks (ANNs) have emerged as a powerful tool for classification tasks due to their ability to outperform traditional methods. Nevertheless, their effectiveness relies heavily on the availability of large, varied, and labeled datasets, which are often not available. To counter this constraint, data augmentation techniques...master thesis 2023
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van Gurp, Samuel (author)Background: Histopathological growth patterns (HGP) are a biomarker for predicting survival and systemic treatment effectiveness in colorectal liver metastasis (CRLM). Currently, HGP assessment in CRLM requires the resection specimen. Predicting the HGP from preoperative medical imaging could allow more personalised care and better outcomes....master thesis 2023
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Lin, Zhi-Yi (author)Human 3D kinematics estimation involves measuring joint angles and body segment scales to quantify and analyze the mechanics of human movements. It has applications in areas such as injury prevention, disease identification, and sports science. Conventional marker-based motion capture methods are expensive both in terms of financial investment...master thesis 2023
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de Boer, Frans (author)In this paper, we investigate the behaviour of current progress prediction methods on the currently used benchmark datasets. We show that the progress prediction methods can fail to extract useful information from visual data on these datasets. Moreover, when the methods fail to extract visual information, memory-based methods adopt a frame...master thesis 2023
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Kielhöfer, Marius (author)The ability to accurately forecast sales volumes holds substantial significance for businesses. Current classical models struggle in capturing the impact of different variables upon the sales volume. These machine learning models are also not applicable to more than one specific product. The Temporal Fusion Transformer (TFT) is implemented to...bachelor thesis 2023
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Farah, Youssef (author)Event cameras are novel bio-inspired sensors that capture motion dynamics with much higher temporal resolution than traditional cameras, since pixels react asynchronously to brightness changes. They are therefore better suited for tasks involving motion such as motion segmentation. However, training event-based networks still represents a...master thesis 2023
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Savu, Ioana (author)Side-channel attacks (SCA) play a crucial role in assessing the security of the implementation of cryp- tographic algorithms. Still, traditional profiled attacks require a nearly identical reference device to the target, limiting their practicality. This thesis focuses on non-profiled SCA, which provides a re- alistic alternative when the...master thesis 2023
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Ries, Maxmillan (author)Training deep learning models for time-series prediction of a target population often requires a substantial amount of training data, which may not be readily available. This work addresses the challenge of leveraging multiple related sources of time series data in the same feature space to improve the prediction performance of a deep learning...master thesis 2023
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DENG, Jing (author)Under future warmer climates, drought events are projected to occur more frequently with increasing impacts in many regions and river basins. This study focuses on exploring the potential of the LSTM deep learning (DL) approach for operational streamflow drought forecasting for the Rhine River at Lobith with a lead time (LT) of up to 46 days. ...master thesis 2023