Characterization of aluminum hydroxide particles from the bayer process using neural network and bayesian classifiers

IEEE Transactions on Neural Networks

Volumn 8, Issue 4, 1997, Pages 919-931

  Zaknich, Anthony ^a,b  

^a UNIVERSITY OF WESTERN AUSTRALIA   (Australia)

^b IEEE   (Australia)

Author keywords

Agglomeration; Aluminum hydroxide; Bayer process; Bayesian classifiers; Crystal size; Expert knowledge; Gaussian model; Morphological processing; Multilayer perceptron; Multiple Gaussian cluster algorithm; Probabilistic neural network

Indexed keywords

BAYESIAN CLASSIFIERS; GRAY SCALE IMAGES;

ALGORITHMS; CLASSIFIERS; HYDRATED ALUMINA; IMAGE PROCESSING; MORPHOLOGY; NEURAL NETWORKS; PROCESS ENGINEERING; SCANNING ELECTRON MICROSCOPY;

METAL REFINERIES;

EID: 0031190871     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/72.595890     Document Type: Article

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