Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Heng-You Wang"'
Publikováno v:
World Journal of Urology. 41:837-841
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::39d6614d3e7d6ed8efdeec4abf8c3eeb
https://doi.org/10.1007/s00345-023-04289-z
https://doi.org/10.1007/s00345-023-04289-z
Publikováno v:
ICMLC
In augmented reality (AR) systems, virtual objects, graphics or texts are added to the real scene to improve the person's perception. Virtual and real information must be aligned strictly in the combination of scenes. The key of augmented reality is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::14a8f2e58b54aa31dadd467095cac7db
https://doi.org/10.1109/icmlc.2016.7873011
https://doi.org/10.1109/icmlc.2016.7873011
Publikováno v:
SPIE Proceedings.
Tracking and registration is one key issue for an augmented reality (AR) system. For the marker-based AR system, the research focuses on detecting the real-time position and orientation of camera. In this paper, we describe a method of tracking and r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::74cc18e93a08a8c8497d46028e1e475d
https://doi.org/10.1117/12.2191823
https://doi.org/10.1117/12.2191823
Publikováno v:
ICMLC
The most important of skew correction for scanned document image is to estimate the skew angle. Traditional methods mostly based on its linear check, such as Hough transformation and so on. However, it is often affected by its texture structure or ot
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::94c617789407b8feb8e4e626874dd2b7
https://doi.org/10.1109/icmlc.2014.7009726
https://doi.org/10.1109/icmlc.2014.7009726
Publikováno v:
ICMLC
In the last decade, Support vector machine (SVM) has been deeply investigated and it is often used in Hilbert space by the measure of Euclidean distance. In this paper, we present the SVM with mahalanobis distance, and the details of how to compute t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8db49ba4122ed892195c47d5b09dbcab
https://doi.org/10.1109/icmlc.2011.6016824
https://doi.org/10.1109/icmlc.2011.6016824
Publikováno v:
2008 International Conference on Machine Learning and Cybernetics.
The support vector machine (SVM) is well understood when kernel functions are positive definite. However, in practice, indefinite kernels arise and demand application in SVM. These indefinite kernels often yield good empirical classification results.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fde9f1fcc4673f274fa542b7b3083b77
https://doi.org/10.1109/icmlc.2008.4620508
https://doi.org/10.1109/icmlc.2008.4620508
Publikováno v:
2011 International Conference on Machine Learning & Cybernetics (ICMLC); 2011, p757-762, 6p
Publikováno v:
2008 International Conference on Machine Learning & Cybernetics; 2008, p774-777, 4p