Please use this identifier to cite or link to this item:
Title: Application of self-organisation neural network for direct shape from shading
Authors: Cheung, WP
Lee, CK
Keywords: 3D shape
Physics-based vision
Self-organising network
Shape from shading
Issue Date: 2001
Source: Neural computing and applications, 2001, v. 10, no. 3, p. 206-213 How to cite?
Journal: Neural Computing and Applications 
Abstract: In this paper, a supervised self-organisation Neural Network (NN) for direct shape from shading is developed. The structure of the NN for the inclined light source model is derived based on the maximum uphill direct shape from shading approach. The major advantage of the NN model presented is the parallel learning or weight evolution for the direct shading. Here the proved convergent learning rule, the rate of convergence and a zero initialisation condition are shown. To increase the rate of convergence, the momentum factor is introduced. Furthermore, the application of the network on IC (Integrated Circuit) component shape reconstruction is presented.
ISSN: 0941-0643
Appears in Collections:Journal/Magazine Article

View full-text via PolyU eLinks SFX Query
Show full item record


Last Week
Last month
Citations as of Aug 14, 2018

Page view(s)

Last Week
Last month
Citations as of Aug 19, 2018

Google ScholarTM


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.