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Dianhui Wang
Researcher at La Trobe University
Publications - 214
Citations - 6390
Dianhui Wang is an academic researcher from La Trobe University. The author has contributed to research in topics: Artificial neural network & Computer science. The author has an hindex of 31, co-authored 198 publications receiving 5150 citations. Previous affiliations of Dianhui Wang include Nanyang Technological University & Northeastern University.
Papers
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Journal ArticleDOI
Learning Pseudo Metric for Intelligent Multimedia Data Classification and Retrieval
TL;DR: This paper develops a framework of learning pseudo metrics (LPM) using neural networks for semantic image classification and retrieval and shows that the LPM has potential application to multimedia information processing.
Proceedings ArticleDOI
Protein sequences classification using radial basis function (RBF) neural networks
TL;DR: A modular neural classifier for protein sequences with improved classification criteria to enhance the performance of single neural classifiers based on a centralized information structure in terms of recognition rate generalization and reliability is presented.
Journal ArticleDOI
Fuzzy rule-based models with randomized development mechanisms
TL;DR: This study investigates performance aspects of randomized rule-base and looks at the performance versus the key components of the models such as the number of rules and the use of the randomized algorithms in the development.
Journal ArticleDOI
Stochastic configuration network ensembles with selective base models
TL;DR: A novel framework for building SCN ensembles by exploring key factors that might potentially affect the generalization performance of the base model and formulating a novel indicator that contains measurement information for the training errors, output weights, and a hidden layer output matrix is proposed.
Journal ArticleDOI
Letter: Learning similarity for semantic images classification
TL;DR: This paper develops a framework of learning similarity (LS) using neural networks for semantic image classification, where a LS-based k-nearest neighbors (k-NN"L) classifier is employed to assign a label to an unknown image according to the majority of k most similar features.