We present a bootstrapping method that uses strong syntactic heuristics to learn semantic lexicons. The three sources of information are appositives, compound nouns, and ISA clauses. We apply heuristics to these syntactic structures, embed them in a bootstrapping architecture, and combine them with co-training. Results on WSJ articles and a pharmaceutical corpus show that this method obtains high precision and finds a large number of terms.

This paper demonstrates that synthetic aperture radar (SAR) images formed using modern spectral estimates can be more accurately segmented than traditional SAR images. Classical FFT based Fourier image formation algorithms produce imagery with strong speckle and sidelobe artifacts that hinder the segmentation process. We show that imagery formed using Capon's minimum variance spectral estimate changes the statistics of the SAR imagery in a way that increases the separation between the various classes of natural terrain. The increased class separation leads to more accurate segmentation. We use the MSTAR dataset to show the statistical changes and demonstrate the improvement in segmentation relative to Fourier imagery.

Constant false alarm rate (CFAR) detection in synthetic aperture radar (SAR) is the first step in most ATR and image exploitation systems. In this paper several CFAR algorithms and their implementation on a 1-D SIMD array processor are investigated. We primarily focus on CFAR algorithms using the Weibull clutter model, but algorithms assuming K-distributed clutter should have similar implementations and runtimes. We show that high resolution SAR requires reference windows much larger than those used in traditional search radars, which permits fast moment based estimation instead of the computationally intensive maximum likelihood parameter estimates. We also extend a fast median filtering algorithm to the order statistic and censored CFAR algorithms. The running times of the CFAR algorithms are listed along with detection results using SAR imagery from the Northrop-Grumman TESAR sensor onboard the Predator unmanned aerial vehicle.