Froth image analysis by use of transfer learning and convolutional neural networks
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Chris Aldrich | Y. Fu | C. Aldrich | Y. Fu
[1] John F. MacGregor,et al. Froth-based modeling and control of flotation processes , 2008 .
[2] Dumitru Erhan,et al. Going deeper with convolutions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[3] Dongyang Dou,et al. Ash content prediction of coarse coal by image analysis and GA-SVM , 2014 .
[4] Matti Pietikäinen,et al. A comparative study of texture measures with classification based on featured distributions , 1996, Pattern Recognit..
[5] C. Aldrich,et al. The Relationship between Froth Image Features and Platinum Flotation Grade , 2010 .
[6] Geoffrey E. Hinton,et al. Learning representations by back-propagating errors , 1986, Nature.
[7] J. Friedman. Regularized Discriminant Analysis , 1989 .
[8] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[9] Bedrich J. Hosticka,et al. A comparison of texture feature extraction using adaptive gabor filtering, pyramidal and tree structured wavelet transforms , 1996, Pattern Recognit..
[10] Chris Aldrich,et al. Multivariate image analysis of realgar–orpiment flotation froths , 2018 .
[11] D. La Rosa,et al. A correlation between Visiofroth(TM) measurements and the performance of a flotation cell , 2007 .
[12] Leo Breiman,et al. Random Forests , 2001, Machine Learning.
[13] Joseph M. Hellerstein,et al. GraphLab: A New Framework For Parallel Machine Learning , 2010, UAI.
[14] Chris Aldrich,et al. Flotation Froth Image Analysis by Use of a Dynamic Feature Extraction Algorithm , 2016 .
[15] Robert M. Haralick,et al. Textural Features for Image Classification , 1973, IEEE Trans. Syst. Man Cybern..
[16] Chris Aldrich,et al. Estimation of platinum flotation grades from froth image data , 2011 .
[17] Edward H. Adelson,et al. Shiftable multiscale transforms , 1992, IEEE Trans. Inf. Theory.
[18] Matti Pietikäinen,et al. Texture classification by center-symmetric auto-correlation, using Kullback discrimination of distributions , 1995, Pattern Recognit. Lett..
[19] J. Kaartinena,et al. Machine-vision-based control of zinc flotation — A case study , 2009 .
[21] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[22] Weihua Gui,et al. Integrated prediction model of bauxite concentrate grade based on distributed machine vision , 2013 .
[23] 张进,et al. Recognition of Flotation Working Conditions through Froth Image Statistical Modeling for Performance Monitoring , 2016 .
[24] James Stephen Marron,et al. Distance‐weighted discrimination , 2015 .
[25] Mostafa Mehdipour-Ghazi,et al. Plant identification using deep neural networks via optimization of transfer learning parameters , 2017, Neurocomputing.
[26] Duncan Fyfe Gillies,et al. Overfitting in linear feature extraction for classification of high-dimensional image data , 2016, Pattern Recognit..
[27] Guangyuan Xie,et al. The concentrate ash content analysis of coal flotation based on froth images , 2016 .
[28] Eero P. Simoncelli,et al. A Parametric Texture Model Based on Joint Statistics of Complex Wavelet Coefficients , 2000, International Journal of Computer Vision.
[29] Chris Aldrich,et al. Online monitoring and control of froth flotation systems with machine vision: A review , 2010 .
[31] Chen Xiao,et al. Complex networks-based texture extraction and classification method for mineral flotation froth images , 2015 .
[32] Marcos E. Orchard,et al. Local models for soft-sensors in a rougher flotation bank , 2003 .
[33] Chris Aldrich,et al. The monitoring of froth surfaces on industrial flotation plants using connectionist image processing techniques , 1995 .
[34] Chris Aldrich,et al. Relationship between surface froth features and process conditions in the batch flotation of a sulphide ore , 1997 .
[35] Jan J. Cilliers,et al. A review of froth flotation control , 2011 .
[36] Chris Aldrich,et al. Monitoring of mineral processing systems by using textural image analysis , 2013 .
[37] Michael S. Bernstein,et al. ImageNet Large Scale Visual Recognition Challenge , 2014, International Journal of Computer Vision.
[38] Joseph E. Gonzalez,et al. GraphLab: A New Parallel Framework for Machine Learning , 2010 .
[39] Liu Jinping. Flotation froth image texture extraction based on LBPV , 2011 .
[40] Mohammad Hamiruce Marhaban,et al. Prediction of the metallurgical performances of a batch flotation system by image analysis and neural networks , 2014 .
[41] Timothée Masquelier,et al. Deep Networks Can Resemble Human Feed-forward Vision in Invariant Object Recognition , 2015, Scientific Reports.
[42] Chris Aldrich,et al. Digital image processing as a tool for on-line monitoring of froth in flotation plants , 1994 .