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Accurate target classification is the keystone of the ship targets recognition in sea battlefields. Aiming at the deficiencies of supervised and unsupervised classified methods, we present a novel scheme called semi-supervised ship target recognition based on affinity propagation (AP). In order to circumvent the problem of choosing initial points, the method introduces affinity propagation clustering...
This paper introduces a novel underwater target classification scheme which recognizes underwater ordnances based on their backscattered Time-Frequency (TF) signatures. The objective is to automatically identify the shape and interior content of sea-disposed underwater munitions and ordnance found in the Hawaiian coastlines. This effort helps in the removal of the above sea-disposals from the ocean...
Safety in railways is mostly achieved by automated operation using a specialized infrastructure. However, many tasks still rely on the decisions and actions of a human crew. Aiming at improving safety in such situations, we present an approach for recognizing railway signals and signs in video sequences taken by an in-vehicle camera. Our approach is based on a model automatically learned from examples,...
A novel fuzzy clustering based target extraction algorithm for FLIR imagery using spatio-temporal technique is presented. Firstly, in temporal domain, we establish the Gauss distribution model of frame difference background by incorporating the motion information of the target. And then, the infrared target region is determined based on change detection mask. Secondly, in spatio domain, the improved...
How to extract effective discriminant features of high-resolution range profile (HRRP) is one of the issues for radar automatic target recognition (RATR). In this paper, a novel method for extracting discriminant features is proposed by using kernel optimal transformation and cluster centers techniques (KOT-CC). In addition, to alleviate the effect of independent noises on the discrimination, we propose...
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