کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4946874 | 1439558 | 2017 | 6 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Probabilistic hypergraph matching based on affinity tensor updating
ترجمه فارسی عنوان
تطبیق هیبرگرافی احتمالی بر اساس تانسور به روز رسانی
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
چکیده انگلیسی
Graph matching is a fundamental problem in artificial intelligence and structural data processing. Hypergraph matching has recently become popular in the graph matching community. Existing hypergraph matching algorithms usually resort to the continuous methods, while the combinatorial nature of hypergraph matching is not well considered. Therefore in this paper, we propose a novel hypergraph matching algorithm by introducing the affinity tensor updating based graduated projection. Specifically, the hypergraph matching problem is first formulated as a combinatorial optimization problem in a high order polynomial form. Then this NP-hard problem is relaxed and interpreted in a probabilistic manner, which is approximately solved by iterative techniques. The updating of the affinity tensor is performed in each iteration, besides the updating of probabilistic assignment vector. Experimental results on both synthetic and real-world datasets witness the effectiveness of the proposed method.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 269, 20 December 2017, Pages 142-147
Journal: Neurocomputing - Volume 269, 20 December 2017, Pages 142-147
نویسندگان
Xu Yang, Zhi-Yong Liu, Hong Qiao, Jian-Hua Su,