evaluation
This dataset acompanies our article titled "Insights into traditional Large Deformation Diffeomorphic Metric Mapping and unsupervised deep-learning for diffeomorphic registration and their evaluation", Computers in Biology and Medicine, 2024. This paper explores the connections between traditional Large Deformation Diffeomorphic Metric Mapping methods and unsupervised deep-learning approaches for non-rigid registration, particularly emphasizing diffeomorphic registration.
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The Web is essential for education and e-learning. This situation has been boosted by migration to distance education due to the SARS-CoV-2. However, students with disabilities have been seriously affected because online teaching is very often not accessible. For this reason, this research aims to evaluate the accessibility of the home pages of the web portals of the Ecuadorian higher education institutions ranked in the Webometrics with the Web Content Accessibility Guidelines (WCAG) 2.1 of the World Wide Web Consortium.
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Decision-makers across many professions are often required to make multi-objective decisions over increasingly larger volumes of data with several competing criteria. Data visualization is a powerful tool for exploring these complex ‘solution spaces’, but there is little research on its ability to support multi-objective decisions. In this paper, we explore the effects of visualization design and data volume on decision quality in multi-objective scenarios with complex trade-offs.
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The plotted graph shows the mean values of the framework evaluation data provided by 10 participants over 8 criteria.
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