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Motion detection - a neural model and its implementation

Pallbo, Robert LU (1994) In LUCS Minor 1
Abstract
A model for motion detection is presented. In this approach, motion is viewed as a stable pattern propagating over the image - a technique that makes the model unusually insensitive to noisy input sequences. The model is based on a neural network and requires spontaneous activation of the nodes in order to be operative. The model has been tested in computer simulations with over 300 000 nodes and more than 6 million connections. A compilation of results from these simulations is also presented.
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Book/Report
publication status
published
subject
keywords
motion detection, neural networks
in
LUCS Minor 1
publisher
[Publisher information missing]
ISSN
1104-1609
language
English
LU publication?
yes
id
b3682425-43bd-4207-956b-c7b766f8205c (old id 526536)
alternative location
http://robert.pallbo.se/academic/Papers/Minor01
date added to LUP
2016-04-04 09:36:21
date last changed
2025-04-04 14:21:53
@techreport{b3682425-43bd-4207-956b-c7b766f8205c,
  abstract     = {{A model for motion detection is presented. In this approach, motion is viewed as a stable pattern propagating over the image - a technique that makes the model unusually insensitive to noisy input sequences. The model is based on a neural network and requires spontaneous activation of the nodes in order to be operative. The model has been tested in computer simulations with over 300 000 nodes and more than 6 million connections. A compilation of results from these simulations is also presented.}},
  author       = {{Pallbo, Robert}},
  institution  = {{[Publisher information missing]}},
  issn         = {{1104-1609}},
  keywords     = {{motion detection; neural networks}},
  language     = {{eng}},
  series       = {{LUCS Minor 1}},
  title        = {{Motion detection - a neural model and its implementation}},
  url          = {{http://robert.pallbo.se/academic/Papers/Minor01}},
  year         = {{1994}},
}