Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Noah Stier"'
Autor:
Arvind Vepa, Andrew Choi, Noor Nakhaei, Wonjun Lee, Noah Stier, Andrew Vu, Greyson Jenkins, Xiaoyan Yang, Manjot Shergill, Moira Desphy, Kevin Delao, Mia Levy, Cristopher Garduno, Lacy Nelson, Wandi Liu, Fan Hung, Fabien Scalzo
Publikováno v:
2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).
Autor:
Chengyuan Xu, Boning Dong, Noah Stier, Curtis McCully, D. Andrew Howell, Pradeep Sen, Tobias Hollerer
We introduce an interactive image segmentation and visualization framework for identifying, inspecting, and editing tiny objects (just a few pixels wide) in large multi-megapixel high-dynamic-range (HDR) images. Detecting cosmic rays (CRs) in astrono
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d3c0c1cdd413abaed132fe022ee331b2
Recent volumetric 3D reconstruction methods can produce very accurate results, with plausible geometry even for unobserved surfaces. However, they face an undesirable trade-off when it comes to multi-view fusion. They can fuse all available view info
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f6ab05973cb00f4fd9465b44bd62aea1
http://arxiv.org/abs/2112.00236
http://arxiv.org/abs/2112.00236
We present 3DVNet, a novel multi-view stereo (MVS) depth-prediction method that combines the advantages of previous depth-based and volumetric MVS approaches. Our key idea is the use of a 3D scene-modeling network that iteratively updates a set of co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e56cb91ccc7062f52102697fbeb37a62
Publikováno v:
Geospatial Informatics X.
In this paper, we present a pipeline and prototype vision system for near-real-time semantic segmentation and classification of objects such as roads, buildings, and vehicles in large high-resolution wide-area real-world aerial LiDAR point-cloud and
Publikováno v:
Medical Imaging 2019: Physics of Medical Imaging.
We introduce a new approach for designing deep learning algorithms for computed tomography applications. Rather than training generically-structured neural network architectures to equivalently perform imaging tasks, we show how to leverage classical
Autor:
Noah Stier, Cristopher Garduno, Sunil Sheth, Gary Duckwiler, Jeffrey Saver, David Liebeskind, Fabien Scalzo
Publikováno v:
Stroke. 47
Background: Imaging the cerebrovasculature using digital subtraction angiography (DSA) is a critical step in the diagnosis and treatment of acute stroke. Interpretation and scoring of these DSA images is usually performed by visual review, introducin
Publikováno v:
BIBM
Hyperperfusion detected on arterial spin labeling (ASL) images acquired after acute stroke onset has been shown to correlate with development of subsequent intracerebral hemorrhage. We present in this study a quantitative hyperperfusion detection mod
Publikováno v:
BIBM
In acute ischemic stroke treatment, prediction of tissue survival outcome plays a fundamental role in the clinical decision-making process, as it can be used to assess the balance of risk vs. possible benefit when considering endovascular clot-retrie
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eae17548162aed41c252e6b722adba7c
https://europepmc.org/articles/PMC5597003/
https://europepmc.org/articles/PMC5597003/
Publikováno v:
Stroke. 46
Introduction: Digital subtraction angiography (DSA) is the gold standard to assess reperfusion during endovascular procedures. Visualization and quantification of changes between successive runs is challenged by patient motion and variations in acqui