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pro vyhledávání: '"Yoo, Youngjin"'
This paper explores the applicability of Image-generation AI in the field of interior architectural design, with a particular focus on automating interior design representation based on design styles. Interior design representation involves a complex
Externí odkaz:
https://library.oapen.org/handle/20.500.12657/89037
This paper suggests the potential application of generative artificial intelligence-based image generation technology in the field of architecture, for early phase shape planning, using the styles of renowned architects. The study employed the follow
Externí odkaz:
https://library.oapen.org/handle/20.500.12657/89041
This paper presents the potential utility of generative artificial intelligence-based light analysis simulation visualization image in the early phase of architectural planning and design. Facilitating the simulation of a building's performance durin
Externí odkaz:
https://library.oapen.org/handle/20.500.12657/89036
Proximity-based contact tracing relies on mobile-device interaction to estimate the spread of disease. ShareTrace is one such approach that improves the efficacy of tracking disease spread by considering direct and indirect forms of contact. In this
Externí odkaz:
http://arxiv.org/abs/2203.12445
Autor:
Ghesu, Florin C., Georgescu, Bogdan, Mansoor, Awais, Yoo, Youngjin, Neumann, Dominik, Patel, Pragneshkumar, Vishwanath, R. S., Balter, James M., Cao, Yue, Grbic, Sasa, Comaniciu, Dorin
Building accurate and robust artificial intelligence systems for medical image assessment requires not only the research and design of advanced deep learning models but also the creation of large and curated sets of annotated training examples. Const
Externí odkaz:
http://arxiv.org/abs/2201.01283
Autor:
Yoo, Youngjin *, Gibson, Eli *, Zhao, Gengyan *, Re, Thomas J. *, Parmar, Hemant, Das, Jyotipriya *, Wang, Hesheng, Kim, Michelle M., Shen, Colette, Lee, Yueh, Kondziolka, Douglas, Ibrahim, Mohannad, Lian, Jun, Jain, Rajan, Zhu, Tong, Comaniciu, Dorin *, Balter, James M., Cao, Yue
Publikováno v:
In International Journal of Radiation Oncology, Biology, Physics July 2024
Autor:
Ghesu, Florin C., Georgescu, Bogdan, Mansoor, Awais, Yoo, Youngjin, Gibson, Eli, Vishwanath, R. S., Balachandran, Abishek, Balter, James M., Cao, Yue, Singh, Ramandeep, Digumarthy, Subba R., Kalra, Mannudeep K., Grbic, Sasa, Comaniciu, Dorin
The interpretation of medical images is a challenging task, often complicated by the presence of artifacts, occlusions, limited contrast and more. Most notable is the case of chest radiography, where there is a high inter-rater variability in the det
Externí odkaz:
http://arxiv.org/abs/2007.04258
Autor:
Barbosa Jr., Eduardo Jose Mortani, Georgescu, Bogdan, Chaganti, Shikha, Aleman, Gorka Bastarrika, Cabrero, Jordi Broncano, Chabin, Guillaume, Flohr, Thomas, Grenier, Philippe, Grbic, Sasa, Gupta, Nakul, Mellot, François, Nicolaou, Savvas, Re, Thomas, Sanelli, Pina, Sauter, Alexander W., Yoo, Youngjin, Ziebandt, Valentin, Comaniciu, Dorin
Objectives: To investigate machine-learning classifiers and interpretable models using chest CT for detection of COVID-19 and differentiation from other pneumonias, ILD and normal CTs. Methods: Our retrospective multi-institutional study obtained 209
Externí odkaz:
http://arxiv.org/abs/2006.04998
Autor:
Liu, Siqi, Georgescu, Bogdan, Xu, Zhoubing, Yoo, Youngjin, Chabin, Guillaume, Chaganti, Shikha, Grbic, Sasa, Piat, Sebastian, Teixeira, Brian, Balachandran, Abishek, RS, Vishwanath, Re, Thomas, Comaniciu, Dorin
The Coronavirus Disease (COVID-19) has affected 1.8 million people and resulted in more than 110,000 deaths as of April 12, 2020. Several studies have shown that tomographic patterns seen on chest Computed Tomography (CT), such as ground-glass opacit
Externí odkaz:
http://arxiv.org/abs/2005.01903