硕士生导师
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学历：博士研究生毕业
学位：工学博士学位
办公地点：犀浦3号教学楼31529
毕业院校：四川大学
学科：电子信息. 软件工程. 计算机应用技术
所在单位：计算机与人工智能学院
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Estimation of the Grain-Size Distribution Using Semisupervised Affinity Propagation
影响因子：2.439
DOI码：10.1061/(ASCE)HE.1943-5584.0001229
所属单位：西南交通大学
发表刊物：Journal of Hydrologic Engineering
刊物所在地：UNITED STATES
关键字：Grain size distribution Image processing Semisupervised affinity propagation model
摘要：The grain-size distribution can play an important role in the sediment movement and the bedload transport rate. However, it still remains an important and challenging issue in the study of river behavior. Accurate estimation of the grain-size distribution is desired, while simultaneously one expects to spend much less time on it. Recently image analysis and machine learning techniques facilitated grain identification and measurement on images. In this paper, a semisupervised affinity propagation model (SAPM) oriented to images method is proposed for automatic extraction of the grain-size distribution based on photographs sampled from Wenchuan and Yingxiu in China where landslides and mudslides usually take place. The model to estimate the grain-size distribution is developed and the corresponding algorithm is illustrated in detail. The experiments are finished in both lab and field, and the proposed algorithm is compared with traditional methods. The proposed algorithm produces much better results in estimating the grain-size distribution in comparison with other image processing methods and manual sieving methods. It is shown that SAPM is an efficient method for precisely estimating the grain-size distribution.
合写作者：Kejun Yang, Xingnian Liu
第一作者：Ruihua Nie
论文类型：学术论文
通讯作者：Hongjun Wang
论文编号：20154801601315
学科门类：工学
一级学科：计算机科学与技术
卷号：Volume 20
ISSN号：1084-0699
是否译文：否
发表时间：2015-12-01