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11#
發(fā)表于 2025-3-23 13:30:48 | 只看該作者
https://doi.org/10.1007/978-3-658-06510-2a spoken word embedded in noise, the proper key to lock the door, smell of coffee, the voice of a favorite singer, the recognition of alphabetic characters, and millions of more tasks that we perform on regular basis.
12#
發(fā)表于 2025-3-23 17:30:59 | 只看該作者
Multilevel Analysis of Attributed Graphs for Explicit Graph Embedding in Vector Spaces,a spoken word embedded in noise, the proper key to lock the door, smell of coffee, the voice of a favorite singer, the recognition of alphabetic characters, and millions of more tasks that we perform on regular basis.
13#
發(fā)表于 2025-3-23 21:37:44 | 只看該作者
14#
發(fā)表于 2025-3-23 23:58:36 | 只看該作者
15#
發(fā)表于 2025-3-24 02:25:28 | 只看該作者
https://doi.org/10.1007/978-3-658-08301-4tion. That is, a set of numerical features describing relevant properties of the pattern are computed and arranged in a vector form. The main advantages of this kind of representation are computational simplicity and a well sound mathematical foundation. Thus, a large number of operations are availa
16#
發(fā)表于 2025-3-24 07:42:38 | 只看該作者
17#
發(fā)表于 2025-3-24 11:26:22 | 只看該作者
18#
發(fā)表于 2025-3-24 17:17:41 | 只看該作者
https://doi.org/10.1057/9781403984678ce learning, and semi-supervised learning. Data clustering often starts with a pairwise similarity graph and then translates into a graph partition problem [19], and thus the quality of the graph essentially determines the clustering quality.
19#
發(fā)表于 2025-3-24 22:29:56 | 只看該作者
Migration, Diversity, and Educationing the diffusion of water molecules as in diffusion tensor imaging [24], face recognition [23, 31], human re-identification [4], texture classification [16], pedestrian detection [39] and action recognition [22, 43].
20#
發(fā)表于 2025-3-24 23:27:18 | 只看該作者
https://doi.org/10.1007/978-3-476-04372-6onent analysis (PCA) [32] pursues the directions of maximum variance for optimal reconstruction. Linear discriminant analysis (LDA) [2], as a supervised algorithm, aims to maximize the inter-class scatter and at the same time minimize the intra-class scatter. Due to utilization of label information,
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