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Titlebook: Scale Space and Variational Methods in Computer Vision; 7th International Co Jan Lellmann,Martin Burger,Jan Modersitzki Conference proceedi

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樓主: 帳簿
31#
發(fā)表于 2025-3-27 00:07:10 | 只看該作者
32#
發(fā)表于 2025-3-27 04:18:19 | 只看該作者
33#
發(fā)表于 2025-3-27 05:58:12 | 只看該作者
Deep Eikonal Solversing scheme which comprises of two components: a local numerical solver and an update scheme. We replace the formulaic local numerical solver with a trained neural network to provide highly accurate estimates of local distances for a variety of different geometries and sampling conditions. Our learni
34#
發(fā)表于 2025-3-27 10:39:32 | 只看該作者
35#
發(fā)表于 2025-3-27 15:59:26 | 只看該作者
Pseudodifferential Inpainting: The Missing Link Between PDE- and RBF-Based Interpolatione other hand, sparse data interpolation is a rich field of its own with different methods such as scattered data interpolation with radial basis functions (RBFs)..The goal of this paper is to establish connections between inpainting with linear shift- and rotation-invariant differential operators an
36#
發(fā)表于 2025-3-27 20:07:45 | 只看該作者
37#
發(fā)表于 2025-3-28 01:42:31 | 只看該作者
38#
發(fā)表于 2025-3-28 06:00:06 | 只看該作者
39#
發(fā)表于 2025-3-28 08:51:43 | 只看該作者
Iterative Sampled Methods for Massive and Separable Nonlinear Inverse Problemst cannot be accessed or is not available all-at-once. In such scenarios (e.g., when massive amounts of data exceed memory capabilities or when data is being streamed), solving inverse problems, especially nonlinear ones, can be very challenging. We focus on separable nonlinear problems, where the ob
40#
發(fā)表于 2025-3-28 11:45:39 | 只看該作者
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