id: 01919224
dt: j
an: 01919224
au: Pasquariello, G.; Satalino, G.; la Forgia, V.; Spilotros, F.
ti: Automatic target recognition for naval traffic control using neural
    networks.
so: Image Vis. Comput. 16, No. 2, 67-73 (1998).
py: 1998
pu: Elsevier, Amsterdam
la: EN
cc: I.2.6 I.4.6 I.5.1 G.1 J.7
ut: computer vision; image processing; pattern recognition; ANN(artificial
    neural network); segmentation; classification; ATR(automatic target
    recognition)
ci: 
li: doi:10.1016/S0262-8856(97)00055-3
ab: Summary: Safety requirements in traffic control stress the importance of
    techniques devoted to automatic tracking of little crafts in harbor
    areas. Changeable sceneries and noise variability make hard the
    recognitions task of an ATR system. In this paper, a modular system
    based on ANNs for the quasi real-time detection of moving targets in
    seaport radar images is proposed. The neural modules resolve both noise
    removal and target identification tasks by processing steps including a
    segmentation, a filtering and a classification phase. The system
    performance have been evaluated on temporal sequences acquired in a
    real maritime environment. (Provider: Leibiger)
rv: