The proposed hybrid approach involves a close integration of high-performance technologies - knowledge-based techniques, neural nets, and parallel hardware are blended together with conventional algorithmic techniques in a well-integrated system architecture. This combination is particularly significant for automatic target recognition (ATR) because the overall target recognition problem involves both pattern recognition and reasoning. The design allows various system functions to utilize the technology that provides the best overall performance. Several innovations are used to achieve these goals. Among these is the use of neural nets at a 'core' level inside the knowledge-based system. The significance of these innovations is that they will, if successful, produce a powerful architecture for building ATR and other high-performance intelligent systems. The emphasis is exclusively on techniques that can be implemetned in real time on modest size, embedded computers, and is specifically oriented towards the need of military applications.


    Access

    Access via TIB

    Check availability in my library


    Export, share and cite



    Title :

    Hybrid approach to automatic target recognition utilizing artificial intelligence and neural nets


    Additional title:

    Eine hybride Lösung für die automatische Zielerkennung unter Verwendung künstlicher Intelligenz und neuronaler Netze


    Contributors:


    Publication date :

    1989


    Size :

    8 Seiten, 2 Bilder, 7 Quellen


    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English





    Neural networks for automatic target recognition

    Chaudhuri, S.P. / Sequeira, C. | Tema Archive | 1990




    Gas Metal Arc Penetration Welding Development Utilizing Neural Nets

    Noruk, J. S. | British Library Conference Proceedings | 1997