Document Details

Document Type : Article In Journal 
Document Title :
Stellar image interpretation system using artificial neural networks: Unipolar function case
نظام تفسير لصور النجوم باستخدام الشبكات العصبية الصناعية: حالة الدالة أحادية القطب
 
Subject : Stellar image interpretation system 
Document Language : English 
Abstract : An artificial neural network based system for interpreting astronomical images has been developed. The system is based on feed-forward Artificial Neural Networks (ANNs) with error back-propagation learning. Knowledge about images of stars, cosmic ray events and noise found in images is used to prepare two sets of input patterns to train and test our approach. The system has been developed and implemented to scan astronomical digital images in order to segregate stellar images from other entities. It has been coded in C language for users of personal computers. An astronomical image of a star cluster from other objects is undertaken as a test case. The obtained results are found to be in very good agreement with those derived from the DAOPHOTII package, which is widely used in the astronomical community. It is proved that our system is simpler, much faster and more reliable. Moreover, no prior knowledge, or initial data from the frame to be analysed is required. 
ISSN : 12102709 
Journal Name : ACTA POLYTECHNICA: Journal of Advanced Engineering 
Volume : 41 
Issue Number : 6 
Publishing Year : 1422 AH
2001 AD 
Article Type : Article 
Added Date : Monday, January 30, 2012 

Researchers

Researcher Name (Arabic)Researcher Name (English)Researcher TypeDr GradeEmail
فرج النجاحيElnagahy, farag ResearcherDoctoratefaragelnagahy@hotmail.com

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