加剧
发表于 2025-3-25 07:20:52
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Saline
发表于 2025-3-25 09:48:32
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Canopy
发表于 2025-3-25 14:37:03
Canonical Correlation Analysis on SPD(,) Manifoldsand has found a multitude of applications in computer vision, medical imaging, and machine learning. The classical formulation assumes that the data live in a pair of . which makes its use in certain important scientific domains problematic. For instance, the set of symmetric positive definite matri
胶水
发表于 2025-3-25 17:05:40
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Hyperopia
发表于 2025-3-25 22:33:51
Robust Estimation for Computer Vision Using Grassmann Manifolds studied for Euclidean spaces and their use has also been extended to Riemannian spaces. In this chapter, we present the necessary mathematical constructs for Grassmann manifolds, followed by two different algorithms that can perform robust estimation on them. In the first one, we describe a nonline
暂停,间歇
发表于 2025-3-26 02:00:40
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jealousy
发表于 2025-3-26 06:05:56
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假装是你
发表于 2025-3-26 11:50:15
Covariance Weighted Procrustes Analysisetely general covariance matrix, extending previous approaches based on factored covariance structures. Procrustes matching is used to compute the Riemannian metric in shape space and is used more widely for carrying out inference such as estimation of mean shape and covariance structure. Rather tha
芳香一点
发表于 2025-3-26 16:41:39
Elastic Shape Analysis of Functions, Curves and Trajectoriesnd trajectories can also have important geometric features, we use shape as an all-encompassing term for the descriptors of curves, scalar functions and trajectories. Our framework relies on functional representation and analysis of curves and scalar functions, by square-root velocity fields (SRVF)
Chagrin
发表于 2025-3-26 18:57:33
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