8 March 2018 The method for froth floatation condition recognition based on adaptive feature weighted
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Proceedings Volume 10609, MIPPR 2017: Pattern Recognition and Computer Vision; 106090B (2018) https://doi.org/10.1117/12.2283129
Event: Tenth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2017), 2017, Xiangyang, China
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.
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Jieran Wang, Jun Zhang, Jinwen Tian, Daimeng Zhang, Xiaomao Liu, "The method for froth floatation condition recognition based on adaptive feature weighted", Proc. SPIE 10609, MIPPR 2017: Pattern Recognition and Computer Vision, 106090B (8 March 2018); doi: 10.1117/12.2283129; https://doi.org/10.1117/12.2283129
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