Title

Neural Hypercolumn Architectures for the Preprocessing of Radiographic Weld Images

Abstract

A general neural hypercolumn architecture is applied to radiographic weld images to locate regions of strong spatial intensity gradients. The hypercolumn output provides information on both the direction and the orientation of local spatial intensity gradients. These outputs can also be used to form an enhanced decimated image which can be processed for feature recognition. Parametric tuning of the architecture is discussed with particular emphasis on the requirements of the application. The performance of this architecture is compared with that of Sobel filters and other edge-detecting convolution masks. The possible representation of these various discrete convolution masks -including hypercolumns - as generalized non-adaptive neurons is also discussed.

Meeting Name

1st Conference on Applications of Artificial Neural Networks (1990: Apr. 18-20, Orlando, FL)

Department(s)

Electrical and Computer Engineering

International Standard Book Number (ISBN)

0000819403458

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 1990 SPIE: The International Society for Optical Engineering, All rights reserved.


Share

 
COinS