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Viering, T.J. (author)This dissertation focuses on safety in machine learning. Our adopted safety notion is related to robustness of learning algorithms. Related to this concept, we touch upon three topics: explainability, active learning and learning curves.<br/><br/>Complex models can often achieve better performance compared to simpler ones. Such larger models are...doctoral thesis 2023
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Pena Pereira, Simon (author)Transforming the global energy sector from fossil-fuel based to renewable energy sources is key to limiting global warming and efficiently achieving climate neutrality. The decentralized nature of the renewable energy system allows private households to install photovoltaic (PV) systems on their rooftops. In this context, planning an efficient...master thesis 2023
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Su, Jiahang (author), Li, Shuai (author), Wolff, Lennard (author), van Zwam, Wim (author), Niessen, W.J. (author), van der Lugt, Aad (author), van Walsum, T. (author)Extracting the cerebral anterior vessel tree of patients with an intracranial large vessel occlusion (LVO) is relevant to investigate potential biomarkers that can contribute to treatment decision making. The purpose of our work is to develop a method that can achieve this from routinely acquired computed tomography angiography (CTA) and...journal article 2023
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Chaudhary, Shivam (author), Prasad Miyapuram, Krishna (author), Lomas, J.D. (author)Entrainment is a phenomenon of phase or temporal matching of one system with that of another system. Human neural activity has been shown to resonate with external auditory stimuli. When we enjoy a piece of music, there is a resonance of brain responses with auditory signals. The crux of music cognition is based on this resonance of musical...conference paper 2023
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Vlekke, Jimmy (author)Global warming causes coral bleaching which threatens the health and existence of coral reefs and therefore also the future of a lot of species, including human beings. Efforts to automate coral reef monitoring using annotated coral images to detect coral bleaching are hindered by the lack of a complete dataset that specifies the health and...master thesis 2022
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Bouwmeester, Rik (author)Nano quadcopters are small, agile, and cheap platforms well suited for deployment in narrow, cluttered environments. Due to their limited payload, nano quadcopters are highly constrained in processing power, rendering conventional vision-based methods for autonomous navigation incompatible. Recent machine learning developments promise high...master thesis 2022
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Apra, Irène (author)Automated reconstruction of detailed semantic 3D city models is challenging due to the need for high-resolution (HR) and large-scale input datasets, the ambiguous definition of the ensuing model, the intricacy of the processing pipeline, and its costs. Furthermore, existing methods mainly focus on geometry rather than semantics. Detailed...master thesis 2022
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Chen, Qilin (author)Convolutional neural networks (CNNs) are often pruned to achieve faster training and inference speed while also requiring less memory. Nevertheless, during computation, most modern GPUs cannot take advantage of the sparsity automatically, especially on networks with unstructured sparsity. Therefore, many libraries that exploit sparsity, have...bachelor thesis 2022
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Collé, Baptiste (author)Most deep learning models fail to generalize in production. Indeed, sometimes data used during training does not completely reflect the deployed environment. The test data is then considered out-of-distribution compared to the training data. In this paper, we focus on out-of-distribution performance for image classification. In fact,...bachelor thesis 2022
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Brockbernd, Bob (author)This research proposes a novel method to classify cognitive behavior based on eye-movement data. Most state-of-the-art approaches use conventional machine learning techniques needing manual feature extraction. This experiment explores the possibility of applying deep learning algorithms to cognitive activity recognition for feature extraction...bachelor thesis 2022
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Băltăreţu, Ana (author)Instance segmentation on data from Dynamic Vision Sensors (DVS) is an important computer vision task that needs to be tackled in order to push the research forward on these types of inputs. This paper aims to show that deep learning based techniques can be used to solve the task of instance segmentation on DVS data. A high performing model was...bachelor thesis 2022
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Bos, Roel (author)Unmanned Ground Vehicle (UGV) navigation in unstructured off-road environments can benefit from accurate traversability estimation. Often, experiments with UGVs use semantic segmentation networks for visual scene understanding. Based on the pixel-wise classification of a semantic segmentation network, the UGV can distinguish traversable from non...master thesis 2022
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van der Heijden, Lars (author)Missions to small bodies are increasingly gaining interest as they might hold the secrets to our solar system’s origin while some are also posing a threat to life on Earth. The small size and irregular shape result in complex dynamics complicating the close-proximity operations. Furthermore, due to the long round-trip time communication delays...master thesis 2022
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Voorhout, Damian (author)Traditional convolutional neural networks exhibit an inherent limitation, they can not adapt their computation to the input while some inputs require less computation to arrive at an accurate prediction than others. Early-exiting setups exploit this fact by only spending as much computation as is necessary and subsequently exiting the sample...master thesis 2022
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Gioia, Gianpaolo (author)The possibility to improve an existing method by making (part of) it learnable is explored in this research. The work that this research extends added prior knowledge to a Convolutional Neural Network (CNN) to improve its performance when dealing with an illumination shift. The method used for the preprocessing, is the color invariant. The...bachelor thesis 2022
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Houbaer, Maikel (author)Earthquakes can do great harm to the environment and people's daily lives. Being able to predict an earthquake moments before it happens could therefore reduce harm and save human lives. Traditional methods have not been successful yet, but with the rise of techniques focused on deep learning, there is a growing interest to apply them to the...bachelor thesis 2022
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Motyka, Tomasz (author)Aside from developing methods to embed the equivariant priors into the architectures, one can also study how the networks learn equivariant properties. In this work, we conduct a study on the influence of different factors on learned equivariance. We propose a method to quantify equivariance and argue why using the correlation to compare...master thesis 2022
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Dong, Y. (author), Patil, Sandeep (author), Farah, H. (author), van Arem, B. (author)Reliable and accurate lane detection is of vital importance for the safe performance of Lane Keeping Assistance and Lane Departure Warning systems. However, under certain challenging peculiar circumstances (e.g., marking degradation, serious vehicle occlusion), it is quite difficult to get satisfactory performance in accurately detecting the...poster 2022
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Vatandaslar, Can (author), Narin, O.G. (author), Abdikan, Saygin (author)Key message: Despite showing a cost-effective potential for quantifying vertical forest structure, the GEDI and ICESat-2 satellite LiDAR missions fall short of the data accuracy standards required by tree- and stand-level forest inventories. Abstract: Tree and stand heights are key inventory variables in forestry, but measuring them manually...journal article 2022
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Tapia, Estefania Alexandra (author), Colomé, Delia Graciela (author), Rueda, José L. (author)Transient stability (TS) and short-term voltage stability (STVS) assessment are of fundamental importance for the operation security of power systems. Both phenomena can be mutually influenced in weak power systems due to the proliferation of power electronic interface devices and the phase-out of conventional heavy machines (e.g., thermal power...journal article 2022