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公开(公告)号：US11195053B2
公开(公告)日：2021-12-07
申请号：US16550015
申请日：2019-08-23
Applicant: Raytheon Company
Inventor： Peter Kim , Ryan Quiller , Jason R. Chaves , Mark S. Berlin , Michael J. Sand
Abstract: A computer architecture for artificial image generation is disclosed. According to some aspects, a computing machine receives a voxel model of a target object. The target object is to be recognized using an image recognizer. The computing machine generates, based on the voxel model, a set of TSB (target shadow background-mask) images of the target object. The computing machine receives, at an auto-encoder, a set of real images of the target object. The computing machine generates, using an auto-encoder and based on the set of real images, one or more artificial images of the target object based on the set of TSB images. The computing machine provides, as output, the generated one or more artificial images of the target object.
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公开(公告)号：US20170039478A1
公开(公告)日：2017-02-09
申请号：US14817685
申请日：2015-08-04
Applicant: Raytheon Company
Inventor： Timothy Campbell , David S. Douglas , Ryan Quiller
CPC classification number: G06N7/005
Abstract: A target estimator that properly conditions measurement variates in the case of a series of sensor measurements collected against a target, a system model that captures visible and hidden stochastic information including but not limited to target state, target identity, and sensor measurements and that marginalizes measurement failure and a dynamic mixed quadrature expression facilitating real-time implementation of the estimator are presented.
Abstract translation: 在针对目标收集的一系列传感器测量的情况下适当地调节测量变量的目标估计器，捕获可见和隐藏的随机信息的系统模型，包括但不限于目标状态，目标身份和传感器测量，并且边缘化测量 介绍了故障和动态混合正交表达，促进了估计器的实时实现。
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公开(公告)号：US10304001B2
公开(公告)日：2019-05-28
申请号：US14817685
申请日：2015-08-04
Applicant: Raytheon Company
Inventor： Timothy Campbell , David S. Douglas , Ryan Quiller
IPC: G06N7/00
Abstract: A target estimator that properly conditions measurement variates in the case of a series of sensor measurements collected against a target, a system model that captures visible and hidden stochastic information including but not limited to target state, target identity, and sensor measurements and that marginalizes measurement failure and a dynamic mixed quadrature expression facilitating real-time implementation of the estimator are presented.
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