Research Output per year
Fingerprint Fingerprint is based on mining the text of the person's scientific documents to create an index of weighted terms, which defines the key subjects of each individual researcher.
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Bayesian networks
Engineering & Materials Science
Neural networks
Engineering & Materials Science
Classifiers
Engineering & Materials Science
Smartphones
Engineering & Materials Science
Evolutionary algorithms
Engineering & Materials Science
Bayesian Networks
Mathematics
Genetic algorithms
Engineering & Materials Science
Mobile devices
Engineering & Materials Science
Network
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Research Output 1990 2019
An ensemble semi-supervised learning method for predicting defaults in social lending
Kim, A. & Cho, S-B., 2019 May 1, In : Engineering Applications of Artificial Intelligence. 81, p. 193-199 7 p.Research output: Contribution to journal › Article
Supervised learning
Labeling
Support vector machines
Labels
Fusion reactions
A personalized context-aware soft keyboard adapted by random forest trained with additional data of same cluster
Jo, S. M. & Cho, S-B., 2019 Jan 1, In : Neurocomputing.Research output: Contribution to journal › Article
Smartphones
Graphical user interfaces
Posture
Hand
Clustering algorithms
A review and empirical analysis of neural networks based exchange rate prediction
Pandey, T. N., Jagadev, A. K., Dehuri, S. & Cho, S-B., 2019 Jan 1, In : Intelligent Decision Technologies. 12, 4, p. 423-439 17 p.Research output: Contribution to journal › Review article
Neural networks
Multilayer neural networks
Time series
Backpropagation
Learning systems
Building a novel classifier based on teaching learning based optimization and radial basis function neural networks for non-imputed database with irrelevant features
Dash, C. S. K., Behera, A. K., Dehuri, S. & Cho, S-B., 2019 Jan 1, In : Applied Computing and Informatics.Research output: Contribution to journal › Article
Open Access
Teaching
Classifiers
Neural networks
Labels
Deep Dense Convolutional Networks for Repayment Prediction in Peer-to-Peer Lending
Kim, J. Y. & Cho, S-B., 2019 Jan 1, International Joint Conference SOCO’18-CISIS’18-ICEUTE’18, Proceedings. Saez, J. A., Corchado, E., Herrero, A., Grana, M., Lopez-Guede, J. M., Etxaniz, O. & Quintian, H. (eds.). Springer Verlag, p. 134-144 11 p. (Advances in Intelligent Systems and Computing; vol. 771).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Neural networks
Convolution
Learning systems