Paper Info
Title
On motion detection through a multi-layer neural network architecture.
Abstract
A neural network model called lateral interaction in accumulative computation for detection of non-rigid objects from motion of any of their parts in indefinite sequences of images is presented. Some biological evidences inspire the model. After introducing the model, the complete multi-layer neural architecture is offered in this paper. The architecture consists of four layers that perform segmentation by gray level bands, accumulative charge computation, charge redistribution by gray level bands and moving object fusion. The lateral interaction in accumulative computation associated learning algorithm is also introduced. Some examples that explain the usefulness of the system we propose are shown at the end of this article.
Year
DOI
Venue
2003
10.1016/S0893-6080(02)00233-2
Neural Networks
Keywords
Field
DocType
neural network model,biological evidence,indefinite sequence,accumulative charge computation,multi-layer neural networks,algorithmic lateral inhibition,charge redistribution,motion detection,gray level band,complete multi-layer neural architecture,accumulative computation,non-rigid object,lateral interaction,multi-layer neural network architecture,lateral inhibition,neural network
Object detection,Motion detection,Segmentation,Algorithm,Network architecture,Image segmentation,Artificial intelligence,Artificial neural network,Machine learning,Grayscale,Mathematics,Computation
Journal
Volume
Issue
ISSN
16
2
0893-6080
Citations 
PageRank 
References 
21
1.08
16
Authors
4
Name
Order
Citations
PageRank
Antonio Fernández-Caballero11317117.99
José Mira220512.90
Miguel A. Fernández338031.84
Ana E. Delgado424316.85