A knowledge-based ("expert") classifier was designed for classifying ship silhouettes generated from forward-looking infrared (FLIR) imagery. A knowledge-base is constructed based on interviews with a U.S. Navy officer along with confirming evidence from Jayne's Fighting Ships. This knowledge provides the means to set-up a ruled-based sequential decision tree or net. The conditions of the production rules deal with silhouette "humps" and their properties such as the number, spacing, relative placement on deck line, and the like. This classifier was applied to a sample consisting of about 500 sample silhouettes distributed about uniformly over eight classes of ship targets. Results were equal or better than results using a more "conventional" classifier.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    A Knowledge-Based Approach To Ship Identification


    Contributors:

    Conference:

    Applications of Artificial Intelligence III ; 1986 ; Orlando,United States


    Published in:

    Publication date :

    1986-03-26





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    A knowledge-based reasoning system for ship identification

    Che, X.M. / Guo, G. / Lu, C.M. | Tema Archive | 1988



    Knowledge-based clustering of ship trajectories using density-based approach

    Liu, Bo / de Souza, Erico N. / Matwin, Stan et al. | IEEE | 2014


    Pirate ship identification system based on marine navigation ship

    YU HOUYAN | European Patent Office | 2022

    Free access