Multiply descent cost competitive learning as an aid for multimedia image processing

Yasuo Matsuyama*, Masayoshi Tan

*この研究の対応する著者

研究成果: Conference contribution

2 被引用数 (Scopus)

抄録

An integration of neural and ordinary computations toward multimedia processing is presented. The handled media is a combination of still images and animations. The neurocomputation here is the multiply descent cost competitive learning. This algorithm generates two types of feature maps. One of them, an optimized grouping pattern of pixels by self-organization, is used. A data-compressed still image can be recovered from this feature map by virtue of the multiply descent cost competitive learning. Next, this map is contorted according to a user's request. At the final step, a movie is virtually generated from the compressed still image via a set of animation tools. Thus, neurocomputation can be a useful item in the toolbox for creating the virtual reality besides the real-world computing.

本文言語English
ホスト出版物のタイトルProceedings of the International Joint Conference on Neural Networks
Place of PublicationPiscataway, NJ, United States
出版社Publ by IEEE
ページ2061-2064
ページ数4
3
ISBN(印刷版)0780314212, 9780780314214
出版ステータスPublished - 1993
外部発表はい
イベントProceedings of 1993 International Joint Conference on Neural Networks. Part 1 (of 3) - Nagoya, Jpn
継続期間: 1993 10 251993 10 29

Other

OtherProceedings of 1993 International Joint Conference on Neural Networks. Part 1 (of 3)
CityNagoya, Jpn
Period93/10/2593/10/29

ASJC Scopus subject areas

  • 工学(全般)

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