Abstract: A system and method for sequential kernel density approximation uses mode propagation to determine mode locations by the mean-shift method and reduce the generated modes. Hessians are calculated corresponding to the mode locations to determine the covariance. Density is approximated to update the density function depending on whether the Hessian is a negative indefinite.

Abstract: The present invention relates to isolated proteins or polypeptides of grapevine leafroll virus (type 2). The encoding DNA molecules either alone in isolated form or in an expression system, a host cell, or a transgenic grape plant are also disclosed. Other aspects of the present invention relates to a method of imparting grapevine leafroll resistance, to grape and tobacco plants by transforming them with the DNA molecules of the present invention, a method of imparting beet yellows virus resistance to a beet plant, a method of imparting tristeza virus resistance to a citrus plant, and a method of detecting the presence of a grapevine leafroll virus, such as GRLaV-2, in a sample.

Abstract: A system and method for modeling a dynamic system using Bayesian filtering, includes a prediction module to predict a state model of the dynamic system, the prediction module generates a prediction density having at least one mode, the state model includes a conditional density function including at least one kernel. Approximating module approximates a measurement probability from a sample set through at least one kernel and an update module updates the conditional density function using the measurement probability and the prediction density. A mode finding and mixture reduction module reduces the number of kernels in the conditional density function.

Abstract: A system and method for detecting and tracking an object is disclosed. A camera captures a video sequence comprised of a plurality of image frames. A processor receives the video sequence and analyzes each image frame to determine if an object is detected. The processor applies one or more classifiers to an object in each image frame and computes a confidence score based on the application of the one or more classifiers to the object. A database stores the one or more classifiers and vehicle training samples. A display displays the video sequence.

Abstract: The present invention relates to isolated proteins or polypeptides of grapevine leafroll virus (type 2). The encoding DNA molecules either alone in isolated form or in an expression system, a host cell, or a transgenic grape plant are also disclosed. Other aspects of the present invention relates to a method of imparting grapevine leafroll resistance to grape and tobacco plants by transforming them with the DNA molecules of the present invention, a method of imparting beet yellows virus resistance to a beet plant, a method of imparting tristeza virus resistance to a citrus plant, and a method of detecting the presence of a grapevine leafroll virus, such as GRLaV-2, in a sample.