Analysing aerial photographs with ADAM
- 2 January 2003
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 3, 49-54
- https://doi.org/10.1109/ijcnn.1992.227038
Abstract
The use of the advanced distributed associative memory (ADAM) in the analysis of features in infrared line scan imagery is described. An ADAM neural network maps an input vector or image to an output vector or image. The ADAM neural network is capable of recognizing features in aerial images using a deterministic noniterative training algorithm. A novel form of weight update allowing a weighted training procedure and a binary runtime system to increase the classification success of ADAM is presented. The results of segmenting urban and field areas, as well as road identification, are discussed Author(s) Smith, G. Dept. of Comput. Sci., York Univ., UK Austin, J.Keywords
This publication has 5 references indexed in Scilit:
- Grey scale N tuple processingPublished by Springer Nature ,1988
- Distributed associative memory for use in scene analysisImage and Vision Computing, 1987
- WISARD·a radical step forward in image recognitionSensor Review, 1984
- Guide to pattern recognition using random-access memoriesIEE Journal on Computers and Digital Techniques, 1979
- Pattern recognition and reading by machinePublished by Association for Computing Machinery (ACM) ,1959