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Biesheuvel, Julian (author)Yes, convolutional neural networks are domain-invariant, albeit to some limited extent. We explored the performance impact of domain shift for convolutional neural networks. We did this by designing new synthetic tasks, for which the network’s task was to map images to their mean, median, standard deviation, and variance pixel intensities. We...bachelor thesis 2021
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Lamon, Julien (author)With an expectation of 8.3 trillion photos stored in 2021 [1], convolutional neural networks (CNN) are beginning to be preeminent in the field of image recognition. However, with this deep neural network (DNN) still being seen as a black box, it is hard to fully employ its capabilities. A need to tune hyperparameters is required to have a robust...bachelor thesis 2021
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Thakoersingh, Ratish (author)This research provides an overview on how training Convolutional Neural Networks (CNNs) on imbalanced datasets affect the performance of the CNNs. Datasets could be imbalanced as a result of several reasons. There are for example naturally less samples of rare diseases. Since the network is trained less on those instances, this might lead to...bachelor thesis 2021
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den Heijer, Remco (author)Does a convolutional neural network (CNN) always have to be deep to learn a task? This is an important question as deeper networks are generally harder to train. We trained shallow and deep CNNs and evaluated their performance on simple regression tasks, such as computing the mean pixel value of an image. For these simple tasks we show that...bachelor thesis 2021
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Di Giuseppe Deininger, Giuseppe (author)During a learning task, keeping a steady attentive state is detrimental for good performance. A person is subject to distraction from different sources, among which distractions originating from within him or herself or from external sources, such as ambient sound. The detection of such distraction can improve the effectiveness of a task by...bachelor thesis 2021
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Kotlicki, Bartlomiej (author)Object detection and recognition is a computer vision problem tackled with techniques such as convolutional neural networks or cascade classifiers. This paper tackles the challenge of using the similar methods in the realm of comics strips characters. We approached the idea of combining cascade classifiers with various convolutional neural...bachelor thesis 2021
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Frolke, Paul (author)In the problem of video summarization, the goal is to select a subset of the input frames conveying the most important information of the input video. The collection of data proves to be a challenging task. In part because there exists a disagreement among human annotators on what segments of a video should be considered important for a summary....bachelor thesis 2021
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Cuperman Coifman, Rafael (author)been given to Human Activity Recognition (HAR) based on signals obtained by IMUs placed on different body parts. This thesis studies the usage of Deep Learning-based models to recognize different football activities in an accurate, robust, and fast manner. Several deep architectures were trained with data captured with IMU sensors placed on...master thesis 2021
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Hejderup, Jacob (author)Recently, it has become popular to use Convolutional Neural Networks (CNNs) in embedded and portable devices. The popularity is based on their high accuracy rate in the field of Computer Vision (CV). However, CNNs are computationally intensive due to the convolutional layer, which accounts for over 90% of the operations. To overcome this problem...master thesis 2021
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Ooms, Eline (author)Lacunes of presumed vascular origin (lacunes) are small lesions in the brain and are an important indicator of cerebral small vessel disease (cSVD). To gain more insight in this disease, obtaining more information about the shape, size and location of lacunes is essential. However, manual segmentation (the voxel-wise labeling of lacunes in a...master thesis 2021
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Pereboom, Leonie (author)The aim of this research is to build a machine learning model in order to predict the success of invasive surgical treatment on a degenerated cervical spine, based on the baseline X-ray images. The purpose of the results of this research is an application in computer-aided diagnostics and treatment planning in the field of neurosurgery. Spinal...master thesis 2021
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Klaoudatos, Dimitrios (author)This MSc thesis presents the development of a viewpoint optimization framework to face the problem of detecting occluded fruits in autonomous harvesting. A Deep Reinforcement Learning (DRL) algorithm is developed in order to train a robotic manipulator to navigate to occlusion-free viewpoints of the tomato-target. Two Convolutional Neural...master thesis 2021
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- Schuit, Berend (author) master thesis 2021
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Rijsdijk, J. (author), Wu, L. (author), Perin, G. (author), Picek, S. (author)Deep learning represents a powerful set of techniques for profiling side-channel analysis. The results in the last few years show that neural network architectures like multilayer perceptron and convolutional neural networks give strong attack performance where it is possible to break targets protected with various coun-termeasures....journal article 2021
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Chen, Y. (author), Goorden, M.C. (author), Beekman, F.J. (author)SPECT imaging with 123I-FP-CIT is used for diagnosis of neurodegenerative disorders like Parkinson's disease. Attenuation correction (AC) can be useful for quantitative analysis of 123I-FP-CIT SPECT. Ideally, AC would be performed based on attenuation maps (μ-maps) derived from perfectly registered CT scans. Such μ-maps, however, are most...journal article 2021
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Adrianus Ewald, V. (author), Sridaran Venkat, Ramanan (author), Asokkumar, Aadhik (author), Benedictus, R. (author), Boller, Christian (author), Groves, R.M. (author)Predictive maintenance, as one of the core components of Industry 4.0, takes a proactive approach to maintain machines and systems in good order to keep downtime to a minimum and the airline maintenance industry is not an exception to this. To achieve this goal, practices in Structural Health Monitoring (SHM) complement the existing Non...journal article 2021
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Li, Z. (author), Mancini, Maria Elisabetta (author), Monizzi, Giovanni (author), Andreini, Daniele (author), Ferrigno, Giancarlo (author), Dankelman, J. (author), De Momi, Elena (author)Cardiologists highlight the need for an intra-operative 3D visualization to assist interventions. The intra-operative 2D X-ray/Digital Subtraction Angiography (DSA) images in the standard clinical workflow limit cardiologists’ views significantly. Compared with image-to-image registration, model-to-image registration is an essential approach...conference paper 2021
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Pastor Serrano, O. (author), Lathouwers, D. (author), Perko, Z. (author)Background and objective: One of the main problems with biomedical signals is the limited amount of patient-specific data and the significant amount of time needed to record the sufficient number of samples needed for diagnostic and treatment purposes. In this study, we present a framework to simultaneously generate and classify biomedical...journal article 2021
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Isufi, E. (author), Pocchiari, Matteo (author), Hanjalic, A. (author)Graph convolutions, in both their linear and neural network forms, have reached state-of-the-art accuracy on recommender system (RecSys) benchmarks. However, recommendation accuracy is tied with diversity in a delicate trade-off and the potential of graph convolutions to improve the latter is unexplored. Here, we develop a model that learns...journal article 2021
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Classification of airborne laser scanning point cloud using point-based convolutional neural networkZhu, Jianfeng (author), Sui, Lichun (author), Zang, Y. (author), Zheng, He (author), Jiang, Wei (author), Zhong, Mianqing (author), Ma, Fei (author)In various applications of airborne laser scanning (ALS), the classification of the point cloud is a basic and key step. It requires assigning category labels to each point, such as ground, building or vegetation. Convolutional neural networks have achieved great success in image classification and semantic segmentation, but they cannot be...journal article 2021