Automatic classification system of fires and smokes from the delta area in Egypt using neural networks
Author
Source
International Journal of Intelligent Computing and Information Sciences
Issue
Vol. 8, Issue 1 (31 Jan. 2008)10 p.
Publisher
Ain Shams University Faculty of Computer and Information Sciences
Publication Date
2008-01-31
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Information Technology and Computer Science
Topics
Abstract EN
An automatic system has been designed to classify fires and smokes from the Delta area in Egypt using Neural Networks (NNs).
The proposed system is trained on the features of the provided image, and is designed to work in an automatic way for finding the best network that has the ability to have the best classification on data is not included in the training data.
It is applied with varying number of layers and neurons in the hidden layers to determine the optimum network architecture.
The system shows an excellent classification of the specified features, the obtained performance is 100% for test data that was collected from the training data, while is 99.6% for test data that was not included in the training data.
The designed system can be carried out on remotely sensed images for classifying any other features.
American Psychological Association (APA)
al-Harbi, A. A.. 2008. Automatic classification system of fires and smokes from the delta area in Egypt using neural networks. International Journal of Intelligent Computing and Information Sciences،Vol. 8, no. 1.
https://search.emarefa.net/detail/BIM-284620
Modern Language Association (MLA)
al-Harbi, A. A.. Automatic classification system of fires and smokes from the delta area in Egypt using neural networks. International Journal of Intelligent Computing and Information Sciences Vol. 8, no. 1 (Jan. 2008).
https://search.emarefa.net/detail/BIM-284620
American Medical Association (AMA)
al-Harbi, A. A.. Automatic classification system of fires and smokes from the delta area in Egypt using neural networks. International Journal of Intelligent Computing and Information Sciences. 2008. Vol. 8, no. 1.
https://search.emarefa.net/detail/BIM-284620
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references.
Record ID
BIM-284620