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Swin-transformer for weak feature matching.
Sci Rep
January 2025
Department of Computer Science and Technology, Qilu University of Technology, No. 3501 Daxue Road, Jinan, 250300, Shandong, China.
Feature matching in computer vision is crucial but challenging in weakly textured scenes due to the lack of pattern repetition. We introduce the SwinMatcher feature matching method, aimed at addressing the issues of low matching quantity and poor matching precision in weakly textured scenes. Given the inherently significant local characteristics of image features, we employ a local self-attention mechanism to learn from weakly textured areas, maximally preserving the features of weak textures.
View Article and Find Full Text PDFDynamic mechanical analysis of alginate/gellan hydrogels under controlled conditions relevant to environmentally sensitive applications.
Carbohydr Polym
March 2025
Institute of Process Systems Engineering, University of Stuttgart, Böblinger Str. 78, 70199 Stuttgart, Germany. Electronic address:
Hydrogels are natural/synthetic polymer-based materials with a large percentage of water content, usually above 80 %, and are suitable for many application fields such as wearable sensors, biomedicine, cosmetics, agriculture, etc. However, their performance is susceptible to environmental changes in temperature, relative humidity, and mechanical deformation due to their aqueous and soft nature. We investigate the mechanical response of both filled and unfilled alginate/gellan hydrogels using a combined axial-torsional rheometric approach with cylindrical samples of large length/diameter ratio under controlled temperature and relative humidity.
View Article and Find Full Text PDFCritique of enhanced power claimed for Quasi-ANCOVA and Dual-Centered ANCOVA.
PLoS One
January 2025
Department of Human Development and Family Science, Oklahoma State University, Stillwater, Oklahoma, United States of America.
Two related methods, Quasi-ANCOVA and Dual-Centered ANCOVA, have recently been suggested as a way to get greater power when analyzing data from a before and after study. Both methods use group-mean centering where the groups are the treatment and comparison groups. Group-mean centering creates a generated regressor problem.
View Article and Find Full Text PDFImpact of Multimodal Prompt Elements on Diagnostic Performance of GPT-4V in Challenging Brain MRI Cases.
Radiology
January 2025
From the Institute of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Strasse 22, Munich 81675, Germany.
Background Studies have explored the application of multimodal large language models (LLMs) in radiologic differential diagnosis. Yet, how different multimodal input combinations affect diagnostic performance is not well understood. Purpose To evaluate the impact of varying multimodal input elements on the accuracy of OpenAI's GPT-4 with vision (GPT-4V)-based brain MRI differential diagnosis.
View Article and Find Full Text PDFAssessing XEN microstent's one-year efficacy: independent of site variability.
Int J Ophthalmol
January 2025
Department of Ophthalmology, University of Leipzig, Liebigstrasse 10-14, Leipzig 04103, Germany.
Aim: To evaluate the short-term efficacy of XEN45 Gel Stent (XEN) implantation for primary open angle glaucoma (POAG) and pseudoexfoliation (PEX) glaucoma across two university eye clinics, aiming to assess the impact of varying center-specific protocols during the first postoperative year.
Methods: We retrospectively examined 282 patients (183 in center 1, 99 in center 2), who underwent XEN microstent implantation for uncontrolled POAG or PEX glaucoma. Parameters including intraocular pressure (IOP), IOP-lowering medication count, best corrected visual acuity (BCVA), and postoperative complications were evaluated over 12mo.
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