Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Chengzhou Tang"'
Autor:
Muhtar Kadirhaz, Yushan Zhang, Nan Zhao, Iltaf Hussain, Sen Xu, Miaomiao Xu, Chengzhou Tang, Wei Zhao, Yi Dong, Yu Fang, Jie Chang
Publikováno v:
Antibiotics, Vol 13, Iss 11, p 1104 (2024)
Objectives: In China, primary healthcare (PHC) facilities have high antibiotic prescribing rates for upper respiratory tract infections (URTIs), which are primarily viral and self-limited. This study aimed to identify the main factors influencing PHC
Externí odkaz:
https://doaj.org/article/ec3b4010935741caa374f071656e807d
Autor:
Muhtar Kadirhaz, Yushan Zhang, Naveel Atif, Wenchen Liu, Wenjing Ji, Nan Zhao, Jin Peng, Sen Xu, Miaomiao Xu, Chengzhou Tang, Yu Fang, Jie Chang
Publikováno v:
Antibiotics, Vol 13, Iss 10, p 923 (2024)
Objectives: Overuse of antibiotics in healthcare remains prevalent and requires urgent attention in China, particularly in primary healthcare (PHC) facilities. This study aimed to describe the patterns of antibiotic prescriptions for acute upper resp
Externí odkaz:
https://doaj.org/article/00aec7ce67084e56a740b8753896de0f
Publikováno v:
IEEE Robotics and Automation Letters. 8:2844-2851
There are increasing interests of studying the video-to-depth (V2D) problem with machine learning techniques. While earlier methods directly learn a mapping from images to depth maps and camera poses, more recent works enforce multi-view geometry con
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6ea4d908f1fd3beecac7163d8bb66592
https://doi.org/10.1109/lra.2023.3260724
https://doi.org/10.1109/lra.2023.3260724
Publikováno v:
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0db683710e50a9cd6502f1fc90d5d90a
https://doi.org/10.1109/cvpr52688.2022.00804
https://doi.org/10.1109/cvpr52688.2022.00804
Publikováno v:
ACM Transactions on Graphics. 38:1-13
360�� video provides an immersive experience for viewers, allowing them to freely explore the world by turning their head. However, creating high-quality 360�� video content can be challenging, as viewers may miss important events by looking
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::836bcf3b372ee0e54b8bf06a78159851
https://doi.org/10.1145/3211889
https://doi.org/10.1145/3211889
Publikováno v:
CVPR
Camera localization aims to estimate 6 DoF camera poses from RGB images. Traditional methods detect and match interest points between a query image and a pre-built 3D model. Recent learning-based approaches encode scene structures into a specific con
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::41a170f8faf3d244f4c79088805e2855
https://doi.org/10.1109/cvpr46437.2021.00187
https://doi.org/10.1109/cvpr46437.2021.00187
Publikováno v:
CVPR
We study the energy minimization problem in low-level vision tasks from a novel perspective. We replace the heuristic regularization term with a learnable subspace constraint, and preserve the data term to exploit domain knowledge derived from the fi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e4f95f0093768aebe6175325ee81f168
https://doi.org/10.1109/cvpr42600.2020.00627
https://doi.org/10.1109/cvpr42600.2020.00627
Publikováno v:
ICCV
This paper presents a scene agnostic neural architecture for camera localization, where model parameters and scenes are independent from each other.Despite recent advancement in learning based methods, most approaches require training for each scene
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::98ec36cc60b4595d4c3a02427a941759
https://doi.org/10.1109/iccv.2019.00013
https://doi.org/10.1109/iccv.2019.00013
Publikováno v:
3DV
Many monocular visual SLAM algorithms are derived from incremental structure-from-motion (SfM) methods. This work proposes a novel monocular SLAM method which integrates recent advances made in global SfM. In particular, we present two main contribut
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3f6731be2a75d4abae8e4c9779e0f6fe
https://doi.org/10.1109/3dv.2017.00027
https://doi.org/10.1109/3dv.2017.00027
Publikováno v:
BMVC
This paper derives a novel linear position constraint for cameras seeing a common scene point, which leads to a direct linear method for global camera translation estimation. Unlike previous solutions, this method deals with collinear camera motion a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5f0fbfceec4e6e80705a7e640809a184
https://doi.org/10.5244/c.29.46
https://doi.org/10.5244/c.29.46