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書(shū)目名稱Graph-Based Representations in Pattern Recognition影響因子(影響力)

書(shū)目名稱Graph-Based Representations in Pattern Recognition影響因子(影響力)學(xué)科排名

書(shū)目名稱Graph-Based Representations in Pattern Recognition網(wǎng)絡(luò)公開(kāi)度

書(shū)目名稱Graph-Based Representations in Pattern Recognition網(wǎng)絡(luò)公開(kāi)度學(xué)科排名

書(shū)目名稱Graph-Based Representations in Pattern Recognition被引頻次

書(shū)目名稱Graph-Based Representations in Pattern Recognition被引頻次學(xué)科排名

書(shū)目名稱Graph-Based Representations in Pattern Recognition年度引用

書(shū)目名稱Graph-Based Representations in Pattern Recognition年度引用學(xué)科排名

書(shū)目名稱Graph-Based Representations in Pattern Recognition讀者反饋

書(shū)目名稱Graph-Based Representations in Pattern Recognition讀者反饋學(xué)科排名

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Modelling Small Deformations of PolycrystalsWe present a direct algorithm that computes a largest common connected induced subgraph of two given graphs. It is based on an efficient generation of the common connected induced subgraphs of the input graphs. Experimental results are provided.

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只看該作者 · 發(fā)表于 2025-3-23 06:08:35

A Vascular Network Growth Estimation Algorithm Using Random Graphs (intussusception). Graph theory is a branch of discrete mathematics that is excellently suited to model vascular networks and to analyze their properties (invariants). A random graph process model can simulate the development of a vascular network that has been modeled using graph theory. The renal

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