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1.发明授权System, method and a computer readable medium for providing an output image 有权系统，方法和用于提供输出图像的计算机可读介质公开(公告)号：US08718333B2
公开(公告)日：2014-05-06
申请号：US12597036
申请日：2008-04-17
申请人： Lior Wolf , Moshe Guttman , Daniel Cohen-Or
发明人： Lior Wolf , Moshe Guttman , Daniel Cohen-Or
IPC分类号： G06K9/00
CPC分类号： G06K9/4671 , G06K9/42 , G06T3/0012 , G06T15/40
摘要： A method for providing an output image, the method includes: determining an importance value for each input pixels out of multiple input pixels of an input image; applying on each of the multiple input pixels a conversion process that is responsive to the importance value of the input pixel to provide multiple output pixels that form the output image; wherein the input image differs from the output image.
摘要翻译： 一种用于提供输出图像的方法，所述方法包括：确定输入图像的多个输入像素中的每个输入像素的重要性值; 在所述多个输入像素中的每一个上施加响应于所述输入像素的重要性值以提供形成所述输出图像的多个输出像素的转换处理; 其中输入图像与输出图像不同。
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2.发明申请SYSTEM, METHOD AND A COMPUTER READABLE MEDIUM FOR PROVIDING AN OUTPUT IMAGE 有权系统，方法和计算机可读介质，用于提供输出图像公开(公告)号：US20110199536A1
公开(公告)日：2011-08-18
申请号：US12597036
申请日：2008-04-17
申请人： Lior Wolf , Moshe Guttman , Daniel Cohen-or
发明人： Lior Wolf , Moshe Guttman , Daniel Cohen-or
IPC分类号： H04N7/01
CPC分类号： G06K9/4671 , G06K9/42 , G06T3/0012 , G06T15/40
摘要： A method for providing an output image, the method includes: determining an importance value for each input pixels out of multiple input pixels of an input image; applying on each of the multiple input pixels a conversion process that is responsive to the importance value of the input pixel to provide multiple output pixels that form the output image; wherein the input image differs from the output image.
摘要翻译： 一种用于提供输出图像的方法，所述方法包括：确定输入图像的多个输入像素中的每个输入像素的重要性值; 在所述多个输入像素中的每一个上施加响应于所述输入像素的重要性值以提供形成所述输出图像的多个输出像素的转换处理; 其中输入图像与输出图像不同。
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3.发明申请SYSTEM AND METHOD FOR STATISTICAL MAPPING BETWEEN GENETIC INFORMATION AND FACIAL IMAGE DATA 有权用于在遗传信息和面部图像数据之间进行统计映射的系统和方法公开(公告)号：US20110206246A1
公开(公告)日：2011-08-25
申请号：US12989021
申请日：2009-04-21
申请人： Lior Wolf , Yonatan Donner , Rona Schniberg
发明人： Lior Wolf , Yonatan Donner , Rona Schniberg
CPC分类号： G06K9/00228 , G06F19/18 , G06F19/24 , G06F19/26 , G06N5/04
摘要： A method and system for statistical mapping between genetic information and facial image data including collecting a multiplicity of sets of genetic information and matching facial image data representing a multiplicity of individuals, representing the genetic information of each of the multiplicity of individuals as a first multidimensional representation, representing the facial image data of each of the multiplicity of individuals as a second multidimensional representation; and inferring correlative, non-causal, statistical relationships between the first multidimensional representations and the second multidimensional representations. A system and method for estimating the likelihood of donor-recipient transplant compatibility using facial images of potential donors, the method including inferring correlative, non-causal, statistical relationships, indicative of transplant compatibility, between multidimensional representations of facial image data of potential donors and a multidimensional representation of information relating to a potential recipient.
摘要翻译： 一种用于遗传信息和面部图像数据之间的统计映射的方法和系统，包括收集多组遗传信息和匹配表示多个个体的面部图像数据，将多个个体中的每一个的遗传信息表示为第一多维表示 将多个个体中的每一个的面部图像数据表示为第二多维表示; 并推断第一个多维表示与第二个多维表示之间的相关性，非因果关系。 一种用于使用潜在供体的面部图像估计供体 - 受体移植物兼容性的可能性的系统和方法，所述方法包括推断潜在供体的面部图像数据的多维表示之间的相关性，非因果关系，指示移植物兼容性的统计关系 与潜在接收者有关的信息的多维表示。
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公开(公告)号：US11727725B2
公开(公告)日：2023-08-15
申请号：US17173720
申请日：2021-02-11
CPC分类号： G06V40/20 , G06T7/246 , G06V10/454 , G06V10/82 , G06V20/41 , G06T2207/30242 , G06V20/44
摘要： A technique and system for counting the number of repetitions of approximately the same action in an input video sequence using 3D convolutional neural networks is disclosed. The proposed system runs online and not on the complete video. It analyzes sequentially blocks of 20 non-consecutive frames. The cycle length within each block is evaluated using a deep network architecture and the information is then integrated over time. A unique property of the disclosed method is that it is shown to successfully train on entirely synthetic data, created by synthesizing moving random patches. It therefore effectively exploits the high generalization capability of deep neural networks. Coupled with a region of interest detection mechanism and a suitable mechanism to identify the time scale of the video, the system is robust enough to handle real world videos collected from youtube and elsewhere, as well as non-video signals such as sensor data revealing repetitious physical movement.
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公开(公告)号：US10922577B2
公开(公告)日：2021-02-16
申请号：US16666390
申请日：2019-10-28
摘要： A technique and system for counting the number of repetitions of approximately the same action in an input video sequence using 3D convolutional neural networks is disclosed. The proposed system runs online and not on the complete video. It analyzes sequentially blocks of 20 non-consecutive frames. The cycle length within each block is evaluated using a deep network architecture and the information is then integrated over time. A unique property of the disclosed method is that it is shown to successfully train on entirely synthetic data, created by synthesizing moving random patches. It therefore effectively exploits the high generalization capability of deep neural networks. Coupled with a region of interest detection mechanism and a suitable mechanism to identify the time scale of the video, the system is robust enough to handle real world videos collected from youtube and elsewhere, as well as non-video signals such as sensor data revealing repetitious physical movement.
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公开(公告)号：US10460194B2
公开(公告)日：2019-10-29
申请号：US15124047
申请日：2015-03-06
摘要： A technique and system for counting the number of repetitions of approximately the same action in an input video sequence using 3D convolutional neural networks is disclosed. The proposed system runs online and not on the complete video. It analyzes sequentially blocks of 20 non-consecutive frames. The cycle length within each block is evaluated using a deep network architecture and the information is then integrated over time. A unique property of the disclosed method is that it is shown to successfully train on entirely synthetic data, created by synthesizing moving random patches. It therefore effectively exploits the high generalization capability of deep neural networks. Coupled with a region of interest detection mechanism and a suitable mechanism to identify the time scale of the video, the system is robust enough to handle real world videos collected from YouTube and elsewhere, as well as non-video signals such as sensor data revealing repetitious physical movement.
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7.发明授权System and method for statistical mapping between genetic information and facial image data 有权遗传信息与面部图像数据之间的统计映射的系统和方法公开(公告)号：US08831293B2
公开(公告)日：2014-09-09
申请号：US12989021
申请日：2009-04-21
申请人： Lior Wolf , Yonatan Donner , Rona Schniberg
发明人： Lior Wolf , Yonatan Donner , Rona Schniberg
CPC分类号： G06K9/00228 , G06F19/18 , G06F19/24 , G06F19/26 , G06N5/04
摘要： A method and system for statistical mapping between genetic information and facial image data including collecting a multiplicity of sets of genetic information and matching facial image data representing a multiplicity of individuals, representing the genetic information of each of the multiplicity of individuals as a first multidimensional representation, representing the facial image data of each of the multiplicity of individuals as a second multidimensional representation; and inferring correlative, non-causal, statistical relationships between the first multidimensional representations and the second multidimensional representations. A system and method for estimating the likelihood of donor-recipient transplant compatibility using facial images of potential donors, the method including inferring correlative, non-causal, statistical relationships, indicative of transplant compatibility, between multidimensional representations of facial image data of potential donors and a multidimensional representation of information relating to a potential recipient.
摘要翻译： 一种用于遗传信息和面部图像数据之间的统计映射的方法和系统，包括收集多组遗传信息和匹配表示多个个体的面部图像数据，将多个个体中的每一个的遗传信息表示为第一多维表示 将多个个体中的每一个的面部图像数据表示为第二多维表示; 并推断第一个多维表示与第二个多维表示之间的相关性，非因果关系。 一种用于使用潜在供体的面部图像估计供体 - 受体移植物兼容性的可能性的系统和方法，所述方法包括推断潜在供体的面部图像数据的多维表示之间的相关性，非因果关系，指示移植物兼容性的统计关系 与潜在接收者有关的信息的多维表示。
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公开(公告)号：US20120224638A1
公开(公告)日：2012-09-06
申请号：US13497263
申请日：2010-09-21
申请人： Lior Wolf
发明人： Lior Wolf
IPC分类号： H04N7/34
CPC分类号： G06K9/4642 , G06K9/00335 , G06K9/6857 , G06T7/20 , G06T2207/20021 , H04N19/503
摘要： A system, computer readable medium and a method for motion detection, the method includes: receiving multiple frames; generating a set of digits for each pixel of multiple pixels of each frame of the multiple frames; wherein each set of digits represents a pixel that belongs to a patch of a frame and represents relationships between (a) first similarities between the patch and a set of patches of a next frame that are located in locations that differ from each other and differ from a location of the patch; and (b) second similarities between the patch and a set of patches of a previous frame that are located in locations that differ from each other and differ from a location of the patch; and processing the sets of digits to detect motion.
摘要翻译： 一种系统，计算机可读介质和运动检测方法，所述方法包括：接收多个帧; 为多个帧的每个帧的多个像素的每个像素生成一组数字; 其中每组数字表示属于帧的补丁的像素，并且表示（a）补丁与位于彼此不同的位置中的下一帧的一组补丁之间的第一相似性之间的关系 补丁的位置; 以及（b）所述贴片和位于彼此不同并且不同于所述贴片位置的位置中的先前框架的一组贴片之间的第二相似度; 并处理数字组以检测运动。
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9.发明申请公开(公告)号：US20200065608A1
公开(公告)日：2020-02-27
申请号：US16666390
申请日：2019-10-28
摘要： A technique and system for counting the number of repetitions of approximately the same action in an input video sequence using 3D convolutional neural networks is disclosed. The proposed system runs online and not on the complete video. It analyzes sequentially blocks of 20 non-consecutive frames. The cycle length within each block is evaluated using a deep network architecture and the information is then integrated over time. A unique property of the disclosed method is that it is shown to successfully train on entirely synthetic data, created by synthesizing moving random patches. It therefore effectively exploits the high generalization capability of deep neural networks. Coupled with a region of interest detection mechanism and a suitable mechanism to identify the time scale of the video, the system is robust enough to handle real world videos collected from youtube and elsewhere, as well as non-video signals such as sensor data revealing repetitious physical movement.
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公开(公告)号：US20170106542A1
公开(公告)日：2017-04-20
申请号：US15293528
申请日：2016-10-14
CPC分类号： B25J13/085 , B25J9/0081 , B25J9/163 , B25J9/1633 , B25J13/02 , B25J13/088 , G05B2219/39312 , G06N3/0454
摘要： A robot having at least one member having at least one controllably actuable articulation, said articulation having at least one torque sensor for providing a torque signal indicative of a torque applied to the articulation, and one angle sensor for providing an angle signal indicative of an angle of actuation of the articulation; the robot further comprising: a controller for controlling said at least one controllably actuable articulation; a first neural network arranged for receiving the torque and angle signals and arranged for providing to the controller a force signal indicating that an external force is applied to said at least one member: a second neural network arranged for receiving the torque and angle signals and arranged for providing to the controller a direction signal indicating the direction along which said external force is applied to said at least one member.
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