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公开(公告)号：US09378426B2
公开(公告)日：2016-06-28
申请号：US14724358
申请日：2015-05-28
Applicant: 3M INNOVATIVE PROPERTIES COMPANY
Inventor： Gabriel A. Biller , Kristopher W. Clover , Masuma W. Henry , Stephen M. June , Brian L. Linzie , Robert D. Lorentz , David M. Mahli , Richard J. Moore , Cristin E. Moran , Tasuku Nakayama , Scott D. Pearson , Dennard J. Powell , Olen Ronning , Guruprasad Somasundaram , Brian J. Stankiewicz , Diane R. Wolk
CPC classification number: G06K9/18 , G06K9/00442 , G06K9/2063 , G06K9/3258
Abstract: At least some aspects of the present disclosure feature systems and methods for note recognition. The note recognition system includes a sensor, a note recognition module, and a note extraction module. The sensor is configured to capture a visual representation of a scene having one or more notes. The note recognition module is coupled to the sensor. The note recognition module is configured to receive the captured visual representation and determine a general boundary of a note from the captured visual representation. The note extraction module is configured to extract content of the note from the captured visual representation based on the determined general boundary of the note.
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公开(公告)号：US20140294236A1
公开(公告)日：2014-10-02
申请号：US14231072
申请日：2014-03-31
Applicant: 3M INNOVATIVE PROPERTIES COMPANY
Inventor： Gabriel A. Biller , Kristopher W. Clover , Masuma W. Henry , Stephen M. June , Brian L. Linzie , Robert D. Lorentz , David M. Mahli , Richard J. Moore , Cristin E. Moran , Tasuku Nakayama , Scott D. Pearson , Dennard J. Powell , Olen Ronning , Guruprasad Somasundaram , Brian J. Stankiewicz , Diane R. Wolk
CPC classification number: G06K9/18 , G06K9/00442 , G06K9/2063 , G06K9/3258
Abstract: At least some aspects of the present disclosure feature systems and methods for note recognition. The note recognition system includes a sensor, a note recognition module, and a note extraction module. The sensor is configured to capture a visual representation of a scene having one or more notes. The note recognition module is coupled to the sensor. The note recognition module is configured to receive the captured visual representation and determine a general boundary of a note from the captured visual representation. The note extraction module is configured to extract content of the note from the captured visual representation based on the determined general boundary of the note.
Abstract translation: 本公开的至少一些方面的特征用于音符识别的系统和方法。 音符识别系统包括传感器，音符识别模块和音符提取模块。 传感器被配置为捕获具有一个或多个音符的场景的视觉表示。 音符识别模块耦合到传感器。 笔记识别模块被配置为接收捕获的视觉表示并且从所捕获的视觉表示中确定音符的一般边界。 笔记提取模块被配置为基于所确定的音符的一般边界从所捕获的视觉表示中提取音符的内容。
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公开(公告)号：US20220243943A1
公开(公告)日：2022-08-04
申请号：US17605393
申请日：2020-04-22
Applicant: 3M INNOVATIVE PROPERTIES COMPANY
Inventor： Saber Taghvaeeyan , Robert W. Shannon , Deepti Pachauri , Brian L. Linzie , Golshan Golnari , Mojtaba Kadkhodaie Elyaderani , Nicolas A. Echeverri
IPC: F24F11/39 , F24F11/58 , F24F11/63 , G05B19/042
Abstract: Systems and methods for monitoring the condition of an air filter installed in an HVAC system and for monitoring the condition of the HVAC system. The monitoring system includes a processing unit configured to receive data representative of at least a first temporal parameter of the HVAC system. The processing unit can process the data to obtain an indication of the condition of the air filter and can also process the data to obtain an indication of the condition of the HVAC system.
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公开(公告)号：US09519916B2
公开(公告)日：2016-12-13
申请号：US13875917
申请日：2013-05-02
Applicant: 3M INNOVATIVE PROPERTIES COMPANY
Inventor： Brian E. Brooks , Brian J. Stankiewicz , Jonathan B. Arthur , Craig G. Markell , Brian L. Linzie
CPC classification number: G06Q30/0244 , G06N99/005 , G06Q10/04 , G06Q30/02
Abstract: The present invention is directed to systems, articles, and computer-implemented methods for assessing effectiveness of communication content and optimizing content distribution to enhance business objectives. Embodiments of the present invention are directed to computer-implemented methods for a computer-implemented method, comprising conducting an experiment using experimental content to determine effectiveness of communication content and executing, while conducting the experiment, a machine learning routine (MLR) using MLR content to enhance an effectiveness metric.
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公开(公告)号：US09131204B2
公开(公告)日：2015-09-08
申请号：US13906858
申请日：2013-05-31
Applicant: 3M INNOVATIVE PROPERTIES COMPANY
Inventor： Brian J. Stankiewicz , Brian E. Brooks , Brian L. Linzie , Nathan J. Anderson , Michael Kelly Canavan , Glenn E. Casner , Timothy J. Gardner , David K. Misemer
CPC classification number: H04N9/87 , G06K9/4628 , G06K9/4671 , G06T11/60
Abstract: Systems and methods for optimizing properties of objects within a scene or achieve a visual goal.
Abstract translation: 用于优化场景中对象的属性或实现视觉目标的系统和方法。
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Patent Agency Ranking
6.发明申请TOUCH SCREEN SENSOR AND PATTERNED SUBSTRATE HAVING OVERLAID MICROPATTERNS WITH LOW VISIBILITY 审中-公开触摸屏传感器和具有低可视性的超大尺寸微型显示器的图案基板公开(公告)号：US20150138151A1
公开(公告)日：2015-05-21
申请号：US14602612
申请日：2015-01-22
Applicant: 3M INNOVATIVE PROPERTIES COMPANY
Inventor： Cristin E. Moran , Matthew H. Frey , Brian L. Linzie , Billy L. Weaver
IPC: G06F3/044
CPC classification number: G06F3/044 , C23F1/02 , C23F1/14 , G06F3/0412 , G06F3/045 , G06F2203/04112 , H05K9/0094 , Y10T428/24802
Abstract: Presently described are articles such as antennas, EMI shields, and touch screen sensors as well as patterned substrates having overlaid micropatterns with low visibility. Also described are methods of determining the visibility of a patterned substrate. In one embodiment, a patterned substrate is described comprising a visible light transparent substrate; and at least two overlaid electrically conductive mesh micropatterns, wherein each mesh has a repeating cell geometry and the combination of overlaid micropatterns has a spatial contrast threshold at a distance of 30000 units of greater than −35 decibels.
Abstract translation: 目前描述的是诸如天线，EMI屏蔽和触摸屏传感器之类的物品，以及具有低可见度的重叠微图案的图案化基板。 还描述了确定图案化衬底的可视性的方法。 在一个实施例中，描述了图案化衬底，其包括可见光透明衬底; 以及至少两个重叠的导电网状微图案，其中每个网格具有重复的单元几何形状，并且重叠的微图案的组合具有在大于-35分贝的30000单位的距离处的空间对比度阈值。
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7.发明授权Systems and methods for evaluating robustness of saliency predictions of regions in a scene 有权用于评估场景中区域显着预测的鲁棒性的系统和方法公开(公告)号：US08811753B2
公开(公告)日：2014-08-19
申请号：US13863879
申请日：2013-04-16
Applicant: 3M Innovative Properties Company
Inventor： Brian J. Stankiewicz , Brian E. Brooks , Brian L. Linzie , Nathan J. Anderson , Michael Kelly Canavan , Glenn E. Casner , Timothy J. Gardner , David K. Misemer
CPC classification number: G06K9/4671 , G06K9/4628 , G06T11/60
Abstract: Systems and methods for evaluating the robustness of objects within a scene or a scene itself.
Abstract translation: 用于评估场景或场景本身中对象的鲁棒性的系统和方法。
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公开(公告)号：US20130259448A1
公开(公告)日：2013-10-03
申请号：US13906858
申请日：2013-05-31
Applicant: 3M INNOVATIVE PROPERTIES COMPANY
Inventor： Brian J. Stankiewicz , Brian E. Brooks , Brian L. Linzie , Nathan J. Anderson , Michael Kelly Canavan , Glenn E. Casner , Timothy J. Gardner , David K. Misemer
IPC: H04N9/87
CPC classification number: H04N9/87 , G06K9/4628 , G06K9/4671 , G06T11/60
Abstract: Systems and methods for optimizing properties of objects within a scene or achieve a visual goal.
Abstract translation: 用于优化场景中对象的属性或实现视觉目标的系统和方法。
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9.发明申请SYSTEMS AND METHODS FOR EVALUATING ROBUSTNESS OF SALIENCY PREDICTIONS OF REGIONS IN A SCENE 有权用于评估场景中区域预测的鲁棒性的系统和方法公开(公告)号：US20130230253A1
公开(公告)日：2013-09-05
申请号：US13863879
申请日：2013-04-16
Applicant: 3M INNOVATIVE PROPERTIES COMPANY
Inventor： Brian J. Stankiewicz , Brian E. Brooks , Brian L. Linzie , Nathan J. Anderson , Michael Kelly Canavan , Glenn E. Casner , Timothy J. Gardner , David K. Misemer
IPC: G06K9/46
CPC classification number: G06K9/4671 , G06K9/4628 , G06T11/60
Abstract: Systems and methods for evaluating the robustness of objects within a scene or a scene itself.
Abstract translation: 用于评估场景或场景本身中对象的鲁棒性的系统和方法。
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公开(公告)号：US10515163B2
公开(公告)日：2019-12-24
申请号：US15834104
申请日：2017-12-07
Applicant: 3M INNOVATIVE PROPERTIES COMPANY
Inventor： Brian E. Brooks , Brian J. Stankiewicz , Brian L. Linzie
Abstract: Systems and methods for improving visual attention models use effectiveness assessment from an environment as feedback to improve visual attention models. The effectiveness assessment uses data indicative of a particular behavior, which is related to visual attention allocation, received from the environment to assess relative effectiveness of the environment on influencing the particular behavior.
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