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This research proposes a nonlinear combination of an ensemble of classifiers to improve pattern recognition performance. A maritime target recognition application is considered. A database of radar range profiles with six ship classes from various aspect angles were created. Five structurally based features are defined on the simulated range profiles. Three kinds of classifiers are used: neural network,...
This research explores the statistical performance of several classifiers (Bayes, nearest neighbor, and a neural network) on a maritime ATR problem. The features employed were derived from range profiles and inspired by the physical structure of the ship targets to maximize the generalizability of the classifiers. The ship targets were created using Pro Engineer (parametric technology corporation),...
A novel approach pertaining to the fast and efficient retrieval and storage of video sequences utilizing MPEG-1/2 motion vectors is presented in this paper. A clip first must be segmented into consistent video segments based on the basic editing effects - cuts, dissolves, and wipes. All group of pictures (GOPs) are then extracted from the clip and decomposed further into I-frames and P-frames (B-frames...
Segmenting videos into meaningful real-world objects remains one of the most challenging image processing research topics. Frame-by-frame object tracking is especially challenging due to the limitations of existing image segmentation algorithms often resulting in inconsistent regions occurring between adjacent frames. This work addresses this problem by introducing an innovative region matching and...
A new method for the temporal segmentation of video sequences into real-world objects is proposed. First, each frame undergoes a color quantization step by matching like colors extracted from the previously processed frame. JSEG's color variance feature and texture features from the gray-level co-occurrence matrix (GLCM) are both extracted from each color-quantized frame and combined to obtain a more...
An adaptive line enhancer is used to obtain estimates of the single sweep steady-state visual evoked potential (SSVEP). The method is seen to enhance the estimated signal to noise ratio of the single sweep SSVEP by as much as 10 dB.<<ETX>>
ConventionaL load forecasting involves the prediction of the mean value of the demand of an electric power system. The mean value of a quantity which is subject to uncertainty does not fully characterize that quantity. In this paper, two well known load forecasting methods are generalized to predict the entire probability density function of the load. Note that the proposed technique is not to calculate...
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