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pro vyhledávání: '"Clarkson P"'
The Cosmological Principle is a cornerstone of the standard model of cosmology and shapes how we view the Universe and our place within it. It is imperative, then, to devise multiple observational tests which can identify and quantify possible violat
Externí odkaz:
http://arxiv.org/abs/2411.08560
Autor:
Karam, Rawan, Dage, Kristen C., Tetarenko, Bailey E., Brumback, McKinley C., Haggard, Daryl, Bahramian, Arash, Hu, Chin-Ping, Neilsen, Joey, Altamirano, Diego, Athukoralalage, Wasundara, Charles, Philip A., Clarkson, William I., Hickox, Ryan C., Kennea, Jamie
The MOOSE (Monitoring Observations of SMC X-1 Excursions) program uses the Neutron Star Interior Composition Explorer Mission (NICER) to monitor the high mass X-ray binary SMC X-1 during its superorbital period excursions. Here we perform X-ray spect
Externí odkaz:
http://arxiv.org/abs/2410.17307
Autor:
Das, Adrito, Sidiqi, Bilal, Mennillo, Laurent, Mao, Zhehua, Brudfors, Mikael, Xochicale, Miguel, Khan, Danyal Z., Newall, Nicola, Hanrahan, John G., Clarkson, Matthew J., Stoyanov, Danail, Marcus, Hani J., Bano, Sophia
Improved surgical skill is generally associated with improved patient outcomes, although assessment is subjective; labour-intensive; and requires domain specific expertise. Automated data driven metrics can alleviate these difficulties, as demonstrat
Externí odkaz:
http://arxiv.org/abs/2409.17025
Autor:
Clarkson, Daniel R., Bull, Lawrence A., Wickramarachchi, Chandula T., Cross, Elizabeth J., Rogers, Timothy J., Worden, Keith, Dervilis, Nikolaos, Hughes, Aidan J.
Regression is a fundamental prediction task common in data-centric engineering applications that involves learning mappings between continuous variables. In many engineering applications (e.g.\ structural health monitoring), feature-label pairs used
Externí odkaz:
http://arxiv.org/abs/2409.04328
Autor:
Zeinoddin, Mona Sheikh, Lena, Chiara, Qu, Jiongqi, Carlini, Luca, Magro, Mattia, Kim, Seunghoi, De Momi, Elena, Bano, Sophia, Grech-Sollars, Matthew, Mazomenos, Evangelos, Alexander, Daniel C., Stoyanov, Danail, Clarkson, Matthew J., Islam, Mobarakol
Robotic-assisted surgery (RAS) relies on accurate depth estimation for 3D reconstruction and visualization. While foundation models like Depth Anything Models (DAM) show promise, directly applying them to surgery often yields suboptimal results. Full
Externí odkaz:
http://arxiv.org/abs/2408.17433
Autor:
Kalbouneh, Basheer, Santiago, Jessica, Marinoni, Christian, Maartens, Roy, Clarkson, Chris, Sarma, Maharshi
Studies show that the model-independent, fully non-perturbative covariant cosmographic approach is suitable for analyzing the local Universe $(z\lesssim 0.1)$. However, accurately characterizing large and inhomogeneous mass distributions requires the
Externí odkaz:
http://arxiv.org/abs/2408.04333
Autor:
Birlo, Manuel, Caramalau, Razvan, Edwards, Philip J. "Eddie", Dromey, Brian, Clarkson, Matthew J., Stoyanov, Danail
We present HUP-3D, a 3D multi-view multi-modal synthetic dataset for hand-ultrasound (US) probe pose estimation in the context of obstetric ultrasound. Egocentric markerless 3D joint pose estimation has potential applications in mixed reality based m
Externí odkaz:
http://arxiv.org/abs/2407.09215
Conformal prediction is a non-parametric technique for constructing prediction intervals or sets from arbitrary predictive models under the assumption that the data is exchangeable. It is popular as it comes with theoretical guarantees on the margina
Externí odkaz:
http://arxiv.org/abs/2407.07700
Autor:
Li, Qi, Shen, Ziyi, Yang, Qianye, Barratt, Dean C., Clarkson, Matthew J., Vercauteren, Tom, Hu, Yipeng
Reconstructing 2D freehand Ultrasound (US) frames into 3D space without using a tracker has recently seen advances with deep learning. Predicting good frame-to-frame rigid transformations is often accepted as the learning objective, especially when t
Externí odkaz:
http://arxiv.org/abs/2407.05767
Upcoming galaxy surveys aim to map the Universe with unprecedented precision, depth and sky coverage. The galaxy bispectrum is a prime source of information as it allows us to probe primordial non-Gaussianity (PNG), a key factor in differentiating va
Externí odkaz:
http://arxiv.org/abs/2407.06301