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公开(公告)号：US09049679B2
公开(公告)日：2015-06-02
申请号：US13731464
申请日：2012-12-31
Inventor： Jae-Bok Park , Duk-Kyun Woo
CPC classification number: H04W64/00 , G01S5/0268 , G01S5/12 , G01S5/14
Abstract: Disclosed herein are a location measurement method and apparatus. The apparatus includes a first grading unit, a first presumed line calculation unit, a second grading unit, a second presumed lined calculating unit, a presumed location calculation unit, and a final location calculation unit. The first grading unit determines the grade of a first RSSI. The first presumed line calculation unit calculates the range of the object from a first node based on the grade of the first RSSI. The second grading unit determines the grade of a second RSSI. The second presumed line calculating unit calculates the range of the object from a second node based on the grade of the second RSSI. The presumed location calculation unit calculates two presumed locations. The final location calculation unit determines one of the two presumed locations to be the final location of the object.
Abstract translation: 这里公开了一种位置测量方法和装置。 该装置包括第一分级单元，第一推测线计算单元，第二分级单元，第二推测内联计算单元，假定位置计算单元和最终位置计算单元。 第一分级单元确定第一RSSI的等级。 第一推测线计算单元基于第一RSSI的等级来计算来自第一节点的对象的范围。 第二分级单元确定第二RSSI的等级。 第二假设线计算单元基于第二RSSI的等级来计算来自第二节点的对象的范围。 推测位置计算单元计算两个推测位置。 最终位置计算单元确定两个推定位置之一作为对象的最终位置。
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公开(公告)号：US20140004878A1
公开(公告)日：2014-01-02
申请号：US13731464
申请日：2012-12-31
Inventor： Jae-Bok Park , Duk-Kyun Woo
IPC: H04W64/00
CPC classification number: H04W64/00 , G01S5/0268 , G01S5/12 , G01S5/14
Abstract: Disclosed herein are a location measurement method and apparatus. The apparatus includes a first grading unit, a first presumed line calculation unit, a second grading unit, a second presumed lined calculating unit, a presumed location calculation unit, and a final location calculation unit. The first grading unit determines the grade of a first RSSI. The first presumed line calculation unit calculates the range of the object from a first node based on the grade of the first RSSI. The second grading unit determines the grade of a second RSSI. The second presumed lined calculating unit calculates the range of the object from a second node based on the grade of the second RSSI. The presumed location calculation unit calculates two presumed locations. The final location calculation unit determines one of the two presumed locations to be the final location of the object.
Abstract translation: 这里公开了一种位置测量方法和装置。 该装置包括第一分级单元，第一推测线计算单元，第二分级单元，第二推测内联计算单元，假定位置计算单元和最终位置计算单元。 第一分级单元确定第一RSSI的等级。 第一推测线计算单元基于第一RSSI的等级来计算来自第一节点的对象的范围。 第二分级单元确定第二RSSI的等级。 第二推测内衬计算单元基于第二RSSI的等级来计算来自第二节点的对象的范围。 推测位置计算单元计算两个推测位置。 最终位置计算单元确定两个推定位置之一作为对象的最终位置。
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公开(公告)号：US12265813B2
公开(公告)日：2025-04-01
申请号：US18098486
申请日：2023-01-18
Inventor： Kyung-Hee Lee , Ji-Young Kwak , Seon-Tae Kim , Jae-Bok Park , Ik-Soo Shin , Chang-Sik Cho
Abstract: An apparatus and method for generating a neural network executable image are disclosed. The apparatus receives user requirements including a default neural network model and training result data for generating a neural network executable image required by a user, checks whether the default neural network model included in the user requirements is capable of being supported in a target system in which the neural network executable image is to be installed, converts the default neural network model into a neural network model executable in the target system, converts the training result data by reconfiguring the data format set of the training result data, and generates a neural network executable image by combining the converted neural network model and the converted training result data.
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公开(公告)号：US12229534B2
公开(公告)日：2025-02-18
申请号：US18098402
申请日：2023-01-18
Inventor： Chang-Sik Cho , Jae-Bok Park , Kyung-Hee Lee , Ji-Young Kwak , Seon-Tae Kim , Ik-Soo Shin
Abstract: Disclosed herein are an apparatus and method for developing a neural network application. The apparatus includes one or more processors and executable memory for storing at least one program executed by the one or more processors. The at least one program receives a target specification and an application specification including user requirements, searches for a neural network model corresponding to the target specification and the application specification in a database, builds an inference engine for performing a neural network operation used by the neural network model, and generates a target image for executing the neural network model to be suitable for a target device using the inference engine.
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