公开(公告)号：US20140279809A1

公开(公告)日：2014-09-18

申请号：US14109059

申请日：2013-12-17

Applicant: Raytheon Company

Inventor： Paul C. Hershey ,  William J. Kyker ,  Donald H. Leonard ,  Jason Dudash ,  Douglas E. Toppin ,  Christopher J. Graham ,  Mu-Cheng Wang ,  Steven A. Davidson

IPC: G06N5/02

CPC classification number: G06N5/025

Abstract: A data broker-reasoner (DBR) system for automating mission planning and execution includes a context originating entity, a reasoner/decision entity, and a plurality of enforcement entities. The context originating entity extracts mission policy information from a variety of source materials, including checklists, manuals, and other documentation. The reasoner/decision entity interprets the mission policy in the context of situational awareness (SA) events to determine which policies should be enforced. Each of the enforcement entities is configured to enforce various policies within the context of a given mission lifecycle phase by providing commands, data, and requests to a plurality of user applications and/or other mission systems. The DBR can operate autonomously or semi-autonomously.

Abstract translation: 用于自动化任务规划和执行的数据代理推理器（DBR）系统包括上下文源实体，推理器/决策实体和多个执行实体。 上下文源实体从各种源材料中提取任务政策信息，包括清单，手册和其他文档。 推理者/决策实体在情境意识（SA）事件的背景下解释任务政策，以确定应执行哪些策略。 每个执行实体被配置为通过向多个用户应用和/或其他任务系统提供命令，数据和请求来在给定的任务生命周期阶段的上下文中执行各种策略。 DBR可以自主或半自主地运行。

公开(公告)号：US20160378789A1

公开(公告)日：2016-12-29

申请号：US14809352

申请日：2015-07-27

Applicant: Raytheon Company

Inventor： Paul C. Hershey ,  Michael P. Sica ,  Jason Dudash ,  Christopher J. Graham

IPC: G06F17/30

CPC classification number: G06F16/29 ,  G06F16/5854

Abstract: A global object detection server reduces the amount of time needed to determine whether an object is present in a collection of images for a geographic area. In particular, the disclosed global object detection server selects one or more object recognition algorithms from a collection of algorithms based on one or more characteristics of the object to be detected. The algorithm results may then be fed back to reduce input data sets from iterative collections for similar regions. The global object detection server can also derive stochastic probabilities for object detection accuracy. Thereafter, one or more visualizations may be created that show confidence levels for the object's probable location in the collection of images.

Abstract translation: 全局对象检测服务器减少了确定对象是否存在于地理区域的图像集合中所需的时间量。 具体地，所公开的全球对象检测服务器基于要检测的对象的一个​​或多个特性从算法集合中选择一个或多个对象识别算法。 然后可以反馈算法结果以减少相似区域的迭代集合的输入数据集。 全局对象检测服务器还可以导出对象检测精度的随机概率。 此后，可以创建一个或多个可视化，其显示对象在图像集合中的可能位置的置信度。