Linguistic instructions learning based on associative memories and its application to a facial model

Hirohide Ushida, Tomohiro Takagi, Toru Yamaguchi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Human learning on linguistic level is superior to other kinds of learning. If a neural network can be trained by natural language instead of numerical data, we can train machines as well as human beings without detailed training data. Conventional neural networks need numerical data to be trained. On the other hand, a linguistic level learning is able to train machines as if they were human beings. In this paper, we propose a linguistic instructions learning method based on an associative memory network, which acquires knowledge from natural language, and we refine a facial expressions model by means of this method.

Original languageEnglish
Title of host publicationProceedings of the International Joint Conference on Neural Networks
PublisherPubl by IEEE
Pages750-753
Number of pages4
ISBN (Print)0780314212, 9780780314214
Publication statusPublished - 1 Dec 1993
EventProceedings of 1993 International Joint Conference on Neural Networks. Part 1 (of 3) - Nagoya, Jpn
Duration: 25 Oct 199329 Oct 1993

Publication series

NameProceedings of the International Joint Conference on Neural Networks
Volume1

Conference

ConferenceProceedings of 1993 International Joint Conference on Neural Networks. Part 1 (of 3)
CityNagoya, Jpn
Period25/10/9329/10/93

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Ushida, H., Takagi, T., & Yamaguchi, T. (1993). Linguistic instructions learning based on associative memories and its application to a facial model. In Proceedings of the International Joint Conference on Neural Networks (pp. 750-753). (Proceedings of the International Joint Conference on Neural Networks; Vol. 1). Publ by IEEE.