Zobrazeno 1 - 10
of 71
pro vyhledávání: '"Tobias Meis"'
Publikováno v:
EJNMMI Physics, Vol 11, Iss 1, Pp 1-21 (2024)
Abstract Purpose Handheld gamma cameras with coded aperture collimators are under investigation for intraoperative imaging in nuclear medicine. Coded apertures are a promising collimation technique for applications such as lymph node localization due
Externí odkaz:
https://doaj.org/article/adc9edd4133a4e839d2e31ba396314a1
Publikováno v:
IEEE Access, Vol 12, Pp 154092-154118 (2024)
The field of deep learning is a rapidly developing research area with numerous applications across multiple domains. Sonar (SOund Navigation And Ranging) processing has traditionally been a field of statistical analysis. However, in the past ten to f
Externí odkaz:
https://doaj.org/article/7e9f5c52638f4a3fa8da3fe5bb3f4935
Publikováno v:
Journal of Theoretical and Applied Electronic Commerce Research, Vol 19, Iss 1, Pp 135-151 (2024)
Alongside natural language processing and computer vision, large learning models have found their way into e-commerce. Especially, for recommender systems and click-through rate prediction, these models have shown great predictive power. In this work
Externí odkaz:
https://doaj.org/article/ea7b54d3deca485ba634147ef12d7a7f
Autor:
Lorenz Balcar, Arpad Mrekva, Bernhard Scheiner, Katharina Pomej, Tobias Meischl, Mattias Mandorfer, Thomas Reiberger, Michael Trauner, Dietmar Tamandl, Matthias Pinter
Publikováno v:
Cancer Imaging, Vol 24, Iss 1, Pp 1-11 (2024)
Abstract Background & aims The value of bleeding prophylaxis and anticoagulation in patients with hepatocellular carcinoma (HCC) and macrovascular tumour invasion (MVI) is unclear. We evaluated the impact of anticoagulation on thrombosis progression,
Externí odkaz:
https://doaj.org/article/01689d25002646a9be02d479c0cabf36
Publikováno v:
e-Journal of Nondestructive Testing, Vol 29, Iss 3 (2024)
Externí odkaz:
https://doaj.org/article/6ea34713f8854483aa1e6b291f6e42d4
Autor:
David Starks, Luis Rojas‐Espaillat, Tobias Meissner, Rachel Elsey, Bing Xu, Maria Koenen, Shelley Feng, Annika VanOosbree, John Slunecka, John Lee, Casey B. Williams
Publikováno v:
Cancer Medicine, Vol 12, Iss 18, Pp 18654-18665 (2023)
Abstract Objectives Phase 1 trial to determine the safety and tolerability of everolimus and niraparib in patients with advanced ovarian and breast malignancies. Results Fourteen heavily pretreated patients were enrolled (12 high‐grade serous ovari
Externí odkaz:
https://doaj.org/article/520ba3ec1b4d4d6f982317b5fb3e7f4a
TEE: Real-Time Purchase Prediction Using Time Extended Embeddings for Representing Customer Behavior
Publikováno v:
Journal of Theoretical and Applied Electronic Commerce Research, Vol 18, Iss 3, Pp 1404-1418 (2023)
Real-time customer purchase prediction tries to predict which products a customer will buy next. Depending on the approach used, this involves using data such as the customer’s past purchases, his or her search queries, the time spent on a product
Externí odkaz:
https://doaj.org/article/60c886cec3f84fb7a059ba164f23a09a
Publikováno v:
Forecasting, Vol 5, Iss 1, Pp 315-335 (2023)
Deep learning models have revolutionized research fields like computer vision and natural language processing by outperforming traditional models in multiple tasks. However, the field of time series analysis, especially time series forecasting, has n
Externí odkaz:
https://doaj.org/article/9fac9444c999435cafbf8a8a8f3115d8
Autor:
Juergen Behr, Christoph Prechtl, Shani Haziraj, Hanno Leuchte, Dorian Bevec, Jens Callegari, Tobias Meis
Publikováno v:
American Journal of Physiology-Lung Cellular and Molecular Physiology. 308:L563-L568
Rationale: A deficiency of the pulmonary vasodilative vasoactive intestinal peptide (VIP) has been suggested to be involved in the pathophysiology of pulmonary hypertension (PH). Supplementation of VIP as an aerosol is hampered by the fact that it is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::26420bd48e6fedaa837f7e65f41136b8
https://doi.org/10.1152/ajplung.00317.2014
https://doi.org/10.1152/ajplung.00317.2014
Publikováno v:
Applied Sciences, Vol 14, Iss 6, p 2267 (2024)
This paper provides an in-depth review of deep learning techniques to address the challenges of odometry and global ego-localization using frequency modulated continuous wave (FMCW) radar sensors. In particular, we focus on the prediction of odometry
Externí odkaz:
https://doaj.org/article/5327cd3f350b444087ea84f0bc5969b0