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The method for froth floatation condition recognition based on adaptive feature weighted
Author(s): Jieran Wang; Jun Zhang; Jinwen Tian; Daimeng Zhang; Xiaomao Liu
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Paper Abstract

The fusion of foam characteristics can play a complementary role in expressing the content of foam image. The weight of foam characteristics is the key to make full use of the relationship between the different features. In this paper, an Adaptive Feature Weighted Method For Froth Floatation Condition Recognition is proposed. Foam features without and with weights are both classified by using support vector machine (SVM).The classification accuracy and optimal equaling algorithm under the each ore grade are regarded as the result of the adaptive feature weighting algorithm. At the same time the effectiveness of adaptive weighted method is demonstrated.

Paper Details

Date Published: 8 March 2018
PDF: 7 pages
Proc. SPIE 10609, MIPPR 2017: Pattern Recognition and Computer Vision, 106090B (8 March 2018); doi: 10.1117/12.2283129
Show Author Affiliations
Jieran Wang, Huazhong Univ. of Science and Technology (China)
Jun Zhang, Huazhong Univ. of Science and Technology (China)
Jinwen Tian, Huazhong Univ. of Science and Technology (China)
Daimeng Zhang, Univ. of Maryland, College Park (United States)
Xiaomao Liu, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 10609:
MIPPR 2017: Pattern Recognition and Computer Vision
Zhiguo Cao; Yuehuang Wang; Chao Cai, Editor(s)

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