Dynamic Neural Field Theory for Motion Perception / The Springer International Series in Engineering and Computer Science Bd.469 (PDF)
(Sprache: Englisch)
Dynamic Neural Field Theory for Motion Perception provides a new theoretical framework that permits a systematic analysis of the dynamic properties of motion perception.
This framework uses dynamic neural fields as a key mathematical concept. The author...
This framework uses dynamic neural fields as a key mathematical concept. The author...
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Dynamic Neural Field Theory for Motion Perception provides a new theoretical framework that permits a systematic analysis of the dynamic properties of motion perception.
This framework uses dynamic neural fields as a key mathematical concept. The author demonstrates how neural fields can be applied for the analysis of perceptual phenomena and its underlying neural processes. Also, similar principles form a basis for the design of computer vision systems as well as the design of artificially behaving systems. The book discusses in detail the application of this theoretical approach to motion perception and will be of great interest to researchers in vision science, psychophysics, and biological visual systems.
This framework uses dynamic neural fields as a key mathematical concept. The author demonstrates how neural fields can be applied for the analysis of perceptual phenomena and its underlying neural processes. Also, similar principles form a basis for the design of computer vision systems as well as the design of artificially behaving systems. The book discusses in detail the application of this theoretical approach to motion perception and will be of great interest to researchers in vision science, psychophysics, and biological visual systems.
Bibliographische Angaben
- Autor: Martin A. Giese
- 2012, 1999, 257 Seiten, Englisch
- Verlag: Springer, New York
- ISBN-10: 1461555817
- ISBN-13: 9781461555810
- Erscheinungsdatum: 06.12.2012
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- Grösse: 33 MB
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