DocumentCode
2534423
Title
Collision prediction via the CNN Universal Machine
Author
Gál, V. ; Roska, T.
Author_Institution
Comput. & Autom. Inst., Hungarian Acad. of Sci., Budapest, Hungary
fYear
2000
fDate
2000
Firstpage
105
Lastpage
110
Abstract
We present an analogic CNN algorithm that estimates the time to an impending collision between an approaching object and the observer. Calculation is based on a context insensitive method, which is well known in neurobiology, using only two specific cues of the expanding two-dimensional image of the looming object
Keywords
analogue processing circuits; cellular neural nets; image processing; neural chips; physiological models; visual perception; CNN Universal Machine; analogic CNN algorithm; collision prediction; context insensitive method; expanding two-dimensional image; Animals; Cellular neural networks; Detectors; Equations; Geometrical optics; Image edge detection; Object detection; Optical arrays; Pixel; Turing machines;
fLanguage
English
Publisher
ieee
Conference_Titel
Cellular Neural Networks and Their Applications, 2000. (CNNA 2000). Proceedings of the 2000 6th IEEE International Workshop on
Conference_Location
Catania
Print_ISBN
0-7803-6344-2
Type
conf
DOI
10.1109/CNNA.2000.876829
Filename
876829
Link To Document