Aug 1, 2015 · Our algorithm uses the 3D SIFT features of 11 scalar fields simultaneously to find matching patterns in the following time steps. This amounts ...

Aug 12, 2015 · We present an approach to pattern matching in 3D multi-field scalar data. Existing pattern matching algorithms work on single scalar or ...

For each vector field pattern, we consider 5 types of trait fields, i.e., Curvature (•), Divergence (•),. Helicity (•), λ2 (•), and Okubo-Weiss (•). In the ...

We present an approach to pattern matching in 3D multi-field scalar data. Existing pattern matching algorithms work on single scalar or vector fields only, ...

Aug 1, 2015 · Our algorithm uses the 3D SIFT features of 11 scalar fields simultaneously to find matching patterns in the following time steps. This amounts ...

Apr 17, 2024 · In this paper, we design a new semi-supervised multi-label feature selection algorithm. First, we construct an initial similarity matrix with supervised ...

An algorithm, multi-feature sparse representation based on adaptive graph constraint (AMFSR), is obtained by solving the optimal objective iteratively.

A sparse sampling strategy utilizing both category-aware and geometry-aware supervisions is introduced. This approach allows the model to distinguish features ...

Apr 7, 2023 · Sparse data refers to datasets with many features with zero values. It can cause problems in different fields, especially in machine ...

Jun 30, 2022 · A multi-manifold based sparse representation (MMSR) algorithm which can preserve the local structure of the datasets in the reconstruction space with multiple ...