| 书目名称 | Dynamic Neural Field Theory for Motion Perception |
| 编辑 | Martin A. Giese |
| 视频video | |
| 丛书名称 | The Springer International Series in Engineering and Computer Science |
| 图书封面 |  |
| 描述 | .Dynamic Neural Field Theory for Motion Perception.provides a new theoretical framework that permits a systematicanalysis of the dynamic properties of motion perception. .This framework uses dynamic neural fields as a key mathematicalconcept. The author demonstrates how neural fields can be applied forthe analysis of perceptual phenomena and its underlying neuralprocesses. Also, similar principles form a basis for the design ofcomputer vision systems as well as the design of artificially behavingsystems. The book discusses in detail the application of thistheoretical approach to motion perception and will be of greatinterest to researchers in vision science, psychophysics, andbiological visual systems. |
| 出版日期 | Book 1999 |
| 关键词 | algorithms; computer vision; perception |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-1-4615-5581-0 |
| isbn_softcover | 978-1-4613-7553-1 |
| isbn_ebook | 978-1-4615-5581-0Series ISSN 0893-3405 |
| issn_series | 0893-3405 |
| copyright | Springer Science+Business Media New York 1999 |
发表于 2025-3-21 19:40:04
