Title
Motion Detection In Asymmetric Neural Networks
Abstract
To make clear the mechanism of the visual movement is important in the visual system. The prominent feature is the nonlinear characteristics as the squaring and rectification functions, which are observed in the retinal and visual cortex networks. Conventional model for motion processing in cortex, is the use of symmetric quadrature functions with Gabor filters. This paper proposes a new motion sensing processing model in the asymmetric networks. To make clear the behavior of the asymmetric nonlinear network, white noise analysis and Wiener kernels are applied. It is shown that the biological asymmetric network with nonlinearities is effective and general for generating the directional movement from the network computations. The qualitative analysis is performed between the asymmetrical network and the conventional quadrature model. The results are applicable to the V1 and MT model of the neural networks in the cortex.
Year
DOI
Venue
2016
10.1007/978-3-319-40663-3_47
ADVANCES IN NEURAL NETWORKS - ISNN 2016
Keywords
Field
DocType
Asymmetrical neural networks, Directional movement, Nonlinear visual pathway, Wiener kernels, Motion detection
Rectification,Nonlinear system,Visual cortex,Motion detection,Pattern recognition,Computer science,White noise,Artificial intelligence,Quadrature (mathematics),Artificial neural network,Computation
Conference
Volume
ISSN
Citations 
9719
0302-9743
0
PageRank 
References 
Authors
0.34
2
4
Name
Order
Citations
PageRank
Naohiro Ishii1461128.62
Toshinori Deguchi23012.88
Masashi Kawaguchi32414.93
Hiroshi Sasaki464.83