Improving the multimodal probabilistic semantic model by ELM classifiers

DOI10.1016/J.JFRANKLIN.2017.08.019zbMath1395.68242OpenAlexW2749552955MaRDI QIDQ1661475

Guoren Wang, Ye Yuan, Yishu Wang, Fangda Guo, Yu Zhang

Publication date: 16 August 2018

Published in: Journal of the Franklin Institute (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jfranklin.2017.08.019

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05) Computing methodologies for image processing (68U10) Information storage and retrieval of data (68P20) Natural language processing (68T50)

Uses Software

• SIFT

Cites Work

• Unnamed Item
• Support-vector networks
• 10.1162/153244303322533214
• 10.1162/jmlr.2003.3.4-5.993
• Unsupervised learning by probabilistic latent semantic analysis

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