Abstract
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.
| Original language | English |
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| Title of host publication | Proceedings of the International Joint Conference on Neural Networks |
| Place of Publication | Piscataway, NJ, United States |
| Publisher | Publ by IEEE |
| Pages | 2061-2064 |
| Number of pages | 4 |
| Volume | 3 |
| ISBN (Print) | 0780314212, 9780780314214 |
| Publication status | Published - 1993 |
| Externally published | Yes |
| Event | Proceedings of 1993 International Joint Conference on Neural Networks. Part 1 (of 3) - Nagoya, Jpn Duration: 1993 Oct 25 → 1993 Oct 29 |
Other
| Other | Proceedings of 1993 International Joint Conference on Neural Networks. Part 1 (of 3) |
|---|---|
| City | Nagoya, Jpn |
| Period | 93/10/25 → 93/10/29 |
ASJC Scopus subject areas
- Engineering(all)