Effectiveness comparison of three types of signatures on the example of the initial selection of aerial images

Authors:
Zbigniew Mikrut
Affiliations:
AGH University of Science and Technology, Institute of Automatics, Krakow, Poland
Venue:
ICAISC'10 Proceedings of the 10th international conference on Artificial intelligence and soft computing: Part I
Year:
2010

Citing 3
Cited 0

Image Processing Using Pulse-Coupled Neural Networks

Image Processing Using Pulse-Coupled Neural Networks
Feature linking via synchronization among distributed assemblies: Simulations of results from cat visual cortex

Neural Computation
PCNN models and applications

IEEE Transactions on Neural Networks

Quantified Score

Hi-index	0.00

Visualization

Abstract

The paper describes, implements and compares three types of pulsed neural networks (ICM and two PCNNs). These networks generated more then 900 image signatures from aerial photos. The signatures have been divided into two classes: suitable and unsuitable for the next stages of photogrammetric analysis. Backpropagation neural networks with various sizes of the hidden layer have been used for the classification of signatures. The effectiveness of the three types of image signatures has been determined based on the recognition results.