1. Lineaments analysis for potential‐fields data using neural networks
- Author
-
Massimo Fossati, Bruno Apolloni, Gabriele Ronchini, and Andrea Zerilli
- Subjects
Artificial neural network ,Pixel ,Computer science ,Binary number ,Consensus function ,Algorithm - Abstract
ture to be analysed (structural characteristies) to determine a consistent set of If, for some p,I pI Y (2) specifying the connections and thresholds of a symmetrical Neural Network of binary threshold units. The Network evolves, starwemarkthe centralpixelof the neighbourhood ting from an initial state, to a system as an edge pixel. configuration with higher values of the We can avoid the problem of fixing the consensus function. Network evolution can be parameter Y, following the classification deterministic or stochastic. method proposed by Ulupinar and Medioni Tests have been conducted on both synthetic (1988). In this case we replace (2) by: and real data with very good results.
- Published
- 1992