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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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Basting, Mark (author)
Multi-label learning is becoming more and moreimportant as real-world data often contains multi-ple labels. The dataset used for learning such aclassifier is of great importance. Acquiring a cor-rectly labelled dataset is however a difficult task.Active learning is a method which can, given anoisy dataset, identify important instances for...
bachelor thesis 2021
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Rozen, Jonathan (author)
Multi-label classification has gained a lot of attraction in the field of computer vision over the past couple of years. Here, each instance belongs to multiple class labels simultaneously. There are numerous methods for Multi-label classification, however all of them make the assumption that either the training images are completely labelled or...
bachelor thesis 2021
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Bilen, H. (author), Zwart, M.D. (author)
With the current increase of user generated data, the need for tools to process large quantities of data is increasing. One of the courses of the Computer Science BSc curriculum is the Big Data Processing course. The Big Data Processing course teaches students ways of doing so. A popular and teached method is using MapReduce, a programming model...
bachelor thesis 2016
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