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Verburg, Corné (author)This thesis addresses the challenge of segmenting ultra-high-resolution images. Limitations of current approaches to segment these are that either detailed spatial contextual information is lost or many redundant computations are necessary. To overcome these issues, we propose a novel approach combining the U-Net architecture with domain...master thesis 2024
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Kappé, Jeroen (author)The city of Amsterdam faces the challenge of monitoring and assessing 200 kilometers of historic quay walls, of which much is deemed to be in poor condition. A key monitoring technique used is photogrammetry resulting in deformation testing. The fundamental data source forming the basis of this deformation analysis is a collection of overlapping...master thesis 2024
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Gunce, Cem (author)Today's electricity supply falls short of current demands, leading to the utilization of gas turbines in both ground based and avionic infrastructures. Nevertheless, these often rely on carbon-based fuels, resulting in escalating CO2 emissions. However, adopting hydrogen as a fuel eliminates carbon emissions. Aside from zero carbon emissions,...master thesis 2024
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Dushatskiy, A. (author)Recently great achievements have been obtained with Artificial Intelligence (AI) methods including human-level performance in such challenging areas as image processing, natural language processing, computational biology, and game playing. Arguably, one of the most societally important application fields of such methods is healthcare. <br/>AI is...doctoral thesis 2023
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Vilakathara, Arjun (author)Accurate segmentation of anatomical structures and abnormalities in medical images is crucial, but manual segmentation is time-consuming and automated approaches lack clinical accuracy. In recent years, active learning approaches that aim to combine automatic segmentation with manual input have gained attention in the field, aiming to reduce the...bachelor thesis 2023
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van Marrewijk, Jonas (author)Segmentation of 3D medical images is useful for various medical tasks. However, fully automated segmentation lacks the accuracy required for medical purposes while manual segmentation is too time-consuming. Therefore, an active learning method can be used to generate an accurate segmentation using less user input. The active learning pipeline...bachelor thesis 2023
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Stellinga, Bram (author)The segmentation of anatomical structures in 3D medical images is crucial for various applications in the field of medical imaging. Fully automated methods often lack accuracy, while manual segmenting requires much time and effort from a user. Due to this, Active Learning approaches are being proposed to solve this by making the method...bachelor thesis 2023
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Kim, Sungjin (author)Although automated segmentation of 3D medical images produce near-ideal results, they encounter limitations and occasional errors, necessitating manual intervention for error correction. Recent studies introduce an active learning pipeline as an efficient solution for this, requiring user corrections only on some of the most uncertain parts of...bachelor thesis 2023
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Budd, Jeremy M. (author), van Gennip, Y. (author), Latz, Jonas (author), Parisotto, Simone (author), Schonlieb, Carola Bibiane (author)Practical image segmentation tasks concern images which must be reconstructed from noisy, distorted, and/or incomplete observations. A recent approach for solving such tasks is to perform this reconstruction jointly with the segmentation, using each to guide the other. However, this work has so far employed relatively simple segmentation...journal article 2023
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Li, Ruohan (author), Dong, Y. (author)Lane detection is crucial for vehicle localization which makes it the foundation for automated driving and many intelligent and advanced driving assistant systems. Available vision-based lane detection methods do not make full use of the valuable features and aggregate contextual information, especially the interrelationships between lane...journal article 2023
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Kostina, Polina (author)The study of the electrophysiological properties of neurons has reached a new level thanks to recent techniques that combine knowledge from different fields of science. For a method such as all-optical electrophysiology, the quality of cell segmentation in the image has one of the critical roles since the accuracy of illumination and...bachelor thesis 2022
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Zeng, Liang (author)Self-supervised contrastive learning has achieved remarkable performance in computer vision. Its success relies on certain priors that vary from different tasks and data at hand, e.g, the object-centric prior implied by ImageNet. For segmentation on complex scenes, researchers have introduced salient objects or auxiliary labels as priors to...master thesis 2022
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Budd, J.M. (author)A large number of modern learning problems involve working with highly interrelated and interconnected data. Graph-based learning is an emerging technique for approaching such problems, by representing this data as a graph (a.k.a. a network). That is, the points of data are represented by the vertices of the graph, and then the edges linking...doctoral thesis 2022
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Bosma, Martijn (author)Deep Neural Networks (DNNs) have the potential to make various clinical procedures more time-efficient by automating medical image segmentation; largely due to their strong, in some cases human-level, performance. The design of the best possible medical image segmentation DNN, however, is task-specific. Neural Architecture Search (NAS), i.e.,...master thesis 2022
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Xing, Xuejun (author), Guo, Jianwei (author), Nan, L. (author), Gu, Qingyi (author), Zhang, Xiaopeng (author), Yan, Dong Ming (author)The point pair feature (PPF) is widely used in industrial applications for estimating 6D poses of known objects from unrecognized point clouds. The key to the success of PPF matching is to establish correct 3D correspondences between the object and the scene, i.e., finding as many valid similar point pairs as possible. Thus, a set of...journal article 2022
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Dushatskiy, A. (author), Lowe, Gerry (author), Bosman, P.A.N. (author), Alderliesten, T. (author)Deep learning algorithms have become the golden standard for segmentation of medical imaging data. In most works, the variability and heterogeneity of real clinical data is acknowledged to still be a problem. One way to automatically overcome this is to capture and exploit this variation explicitly. Here, we propose an approach that improves...conference paper 2022
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Dushatskiy, A. (author), Alderliesten, T. (author), Bosman, P.A.N. (author)Neural Architecture Search (NAS) has recently become a topic of great interest. However, there is a potentially impactful issue within NAS that remains largely unrecognized: noise. Due to stochastic factors in neural network initialization, training, and the chosen train/validation dataset split, the performance evaluation of a neural network...conference paper 2022
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Meister, S. (author), Wermes, Mahdieu A.M. (author), Stüve, Jan (author), Groves, R.M. (author)The aerospace industry has established the Automated Fiber Placement process as a common technique for manufacturing fibre reinforced components. In this process multiple composite tows are placed simultaneously onto a tool. Currently in such processes manual testing requires often up to 50% of the manufacturing duration. Moreover, the...review 2021
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Dai, Pengwen (author), Li, Y. (author), Zhang, Hua (author), Li, Jingzhi (author), Cao, Xiaochun (author)Scene text detection has attracted increasing concerns with the rapid development of deep neural networks in recent years. However, existing scene text detectors may overfit on the public datasets due to the limited training data, or generate inaccurate localization for arbitrary-shape scene texts. This paper presents an arbitrary-shape scene...journal article 2021
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Yousefi, Sahar (author), Sokooti, Hessam (author), Elmahdy, Mohamed S. (author), Lips, Irene M. (author), Shalmani, Mohammad T.Manzuri (author), Zinkstok, Roel T. (author), Dankers, Frank J.W.M. (author), Staring, M. (author)Manual or automatic delineation of the esophageal tumor in CT images is known to be very challenging. This is due to the low contrast between the tumor and adjacent tissues, the anatomical variation of the esophagus, as well as the occasional presence of foreign bodies (e.g. feeding tubes). Physicians therefore usually exploit additional...journal article 2021