Chunru Dong
According to our database1,
Chunru Dong
authored at least 22 papers
between 2004 and 2025.
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Bibliography
2025
A deep spatiotemporal interaction network for multimodal sentimental analysis and emotion recognition.
Inf. Sci., 2025
2023
Asia Pac. J. Oper. Res., October, 2023
Asia Pac. J. Oper. Res., August, 2023
2022
Knowl. Based Syst., 2022
Deep Emotional Arousal Network for Multimodal Sentiment Analysis and Emotion Recognition.
Inf. Fusion, 2022
A model with pseudo-label correction and distribution alignment for image clustering.
Comput. Electr. Eng., 2022
2020
Int. J. Mach. Learn. Cybern., 2020
2018
A Novel Approach to Face Verification Based on Second-Order Face-Pair Representation.
Complex., 2018
2015
A Study on Relationship Between Generalization Abilities and Fuzziness of Base Classifiers in Ensemble Learning.
IEEE Trans. Fuzzy Syst., 2015
Int. J. Mach. Learn. Cybern., 2015
J. High Speed Networks, 2015
2014
An improved differential evolution and its application to determining feature weights in similarity-based clustering.
Neurocomputing, 2014
2013
An improved differential evolution and its application to determining feature weights in similarity based clustering.
Proceedings of the International Conference on Machine Learning and Cybernetics, 2013
2011
A survey of the initialization of centers and widths in radial basis function network for classification.
Proceedings of the International Conference on Machine Learning and Cybernetics, 2011
2010
Proceedings of the International Conference on Machine Learning and Cybernetics, 2010
Proceedings of the International Conference on Machine Learning and Cybernetics, 2010
2009
IEEE Trans. Fuzzy Syst., 2009
2008
Proceedings of the IEEE International Conference on Systems, 2008
2007
Neurocomputing, 2007
A sample selection algorithm in fuzzy decision tree induction and its theoretical analyses.
Proceedings of the IEEE International Conference on Systems, 2007
2005
Proceedings of the Advances in Machine Learning and Cybernetics, 2005
2004
A study on generalization capability of weighted fuzzy production rules with maximum entropy.
Proceedings of the IEEE International Conference on Systems, 2004