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公开(公告)号：US20230394116A1
公开(公告)日：2023-12-07
申请号：US17847329
申请日：2022-06-23
CPC分类号： G06K9/6267 , G06T13/40 , G06K9/6223 , G06K9/6219 , G06T7/246
摘要： A method for automatically classifying transition motion includes following steps performed by a computing device: obtaining a plurality of transition motions, with each transition motion being associated with a source motion, a destination motion, and a transition mechanism converting the source motion into the destination motion; extracting a property vector from each transition motion and thereby generating a plurality of property vectors, wherein each property vector includes a plurality of transition properties; and performing a clustering algorithm according to the property vectors to generate a plurality of transition types.
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公开(公告)号：US11783917B2
公开(公告)日：2023-10-10
申请号：US16826126
申请日：2020-03-20
申请人： Illumina, Inc.
IPC分类号： G06V10/82 , G06K9/62 , G06N3/08 , G16B40/00 , G06N3/04 , G06F16/907 , G06N3/084 , G06N7/00 , G06V10/75 , G06N5/046
CPC分类号： G06K9/6218 , G06F16/907 , G06K9/628 , G06K9/6222 , G06K9/6232 , G06K9/6256 , G06K9/6262 , G06K9/6267 , G06K9/6277 , G06N3/04 , G06N3/08 , G06N3/084 , G06N7/005 , G06V10/751 , G06V10/82 , G16B40/00 , G06N5/046
摘要： The technology disclosed processes input data through a neural network and produces an alternative representation of the input data. The input data includes per-cycle image data for each of one or more sequencing cycles of a sequencing run. The per-cycle image data depicts intensity emissions of one or more analytes and their surrounding background captured at a respective sequencing cycle. The technology disclosed processes the alternative representation through an output layer and producing an output and base calls one or more of the analytes at one or more of the sequencing cycles based on the output.
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公开(公告)号：US11696735B2
公开(公告)日：2023-07-11
申请号：US17314758
申请日：2021-05-07
发明人： Andrew J. Buckler , Mark A. Buckler
IPC分类号： G06T7/00 , G06K9/62 , G06T5/00 , G06T11/00 , A61B6/03 , A61B6/00 , G06T7/11 , G06V10/44 , G06V30/262
CPC分类号： G06T7/0012 , A61B6/032 , A61B6/463 , A61B6/481 , A61B6/504 , A61B6/5217 , A61B6/5294 , G06K9/6228 , G06K9/6267 , G06K9/6274 , G06T5/003 , G06T7/11 , G06T11/001 , G06V10/454 , G06V10/457 , G06V30/274 , A61B6/5258 , G06K9/6257 , G06T2207/10081 , G06T2207/10088 , G06T2207/10101 , G06T2207/10104 , G06T2207/10108 , G06T2207/10132 , G06T2207/20016 , G06T2207/20081 , G06T2207/20084 , G06T2207/20104 , G06T2207/30096 , G06T2207/30104 , G06V2201/03
摘要： Systems and methods for analyzing pathologies utilizing quantitative imaging are presented herein. Advantageously, the systems and methods of the present disclosure utilize a hierarchical analytics framework that identifies and quantify biological properties/analytes from imaging data and then identifies and characterizes one or more pathologies based on the quantified biological properties/analytes. This hierarchical approach of using imaging to examine underlying biology as an intermediary to assessing pathology provides many analytic and processing advantages over systems and methods that are configured to directly determine and characterize pathology from underlying imaging data.
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公开(公告)号：US20230214452A1
公开(公告)日：2023-07-06
申请号：US17566993
申请日：2021-12-31
申请人： Crosscope Inc.
IPC分类号： G06K9/62 , G06F40/205 , G06T7/11 , G06F3/0481
CPC分类号： G06K9/6257 , G06K9/6267 , G06F40/205 , G06K9/6253 , G06T7/11 , G06F3/0481 , G06T2200/24 , G06T2207/20021 , G06T2207/20081
摘要： Systems and methods describe dwell time recording of digital image review sessions. The system displays, at a user interface (UI), a portion of an image on at least one monitor, where the image is segmented into a multitude of patches. The system then receives UI events involving a change in the currently displayed patches. For each of the UI events, the system records one or more dwell times representing durations for which the current patches of the image were displayed. The system also receives a report associated with the image review session, and processes the text of the report to determine a classification label for the image. Finally, the system trains a machine learning model, using at least the recorded dwell times and the classification label for the image.
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5.发明授权公开(公告)号：US11670036B2
公开(公告)日：2023-06-06
申请号：US16928653
申请日：2020-07-14
CPC分类号： G06T15/08 , G06K9/6256 , G06K9/6267 , G06T7/0002 , G06T15/005 , G06T2207/10081
摘要： An automatic threat recognition system and method is disclosed for scanning the x-ray CT image of an article to identify the objects of interest (OOIs) contained within the article, which are otherwise not always quickly apparent or discernable to an individual. The system uses a computer to receive information from two-dimensional (2D) image slices from a reconstructed computed tomography (CT) scan image and to produce a plurality of voxels for each slice of the 2D image. The computer analyzes the voxels to create a likelihood map (LM) representing likelihoods that voxels making up the CT image are associated with a material of interest (MOI). The computer further analyzes the LM to construct neighborhoods of voxels within the LM, and classifies each voxel neighborhood based on its features, thereby decluttering the LM to facilitate the process of connecting voxels of a like MOI together to form segments. The computer classifies each candidate segment based on its features, thereby identifying those segments that correspond to objects of interest.
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6.发明公开公开(公告)号：US20230169125A1
公开(公告)日：2023-06-01
申请号：US17820221
申请日：2022-08-16
发明人： Yasuki TANABE
IPC分类号： G06F16/906 , G06K9/62
CPC分类号： G06F16/906 , G06K9/6267
摘要： An information processing system according to one embodiment includes information processing devices. Each device includes one or more hardware processors functioning to accept input of processing data and detect whether a classification of the processing data is a target classification or a non-target classification. The target classification is a target of first processing. The non-target classification is not a target of the first processing. The hardware processors function to execute the first processing on the processing data upon detection of the classification of the processing data being the target classification. The hardware processors function to determine, as a destination device, an information processing device serving to perform processing on data of the non-target classification. The determination is made upon detection of the classification of the processing data being the non-target classification. The hardware processors function to transmit the processing data to the destination device.
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公开(公告)号：US11657527B2
公开(公告)日：2023-05-23
申请号：US16424363
申请日：2019-05-28
申请人： X Development LLC
发明人： Yunfei Bai , Yuanzheng Gong
IPC分类号： H04N5/268 , H04N5/247 , H04N5/232 , H04N13/111 , H04N13/161 , H04N13/282 , B25J9/16 , G06T7/12 , G06T7/521 , G06T7/13 , G06K9/62 , G06T5/00
CPC分类号： B25J9/1697 , B25J9/1661 , G06K9/6267 , G06T5/008 , G06T7/12 , G06T7/13 , G06T7/521 , H04N5/247 , G06T2207/10024 , G06T2207/10028 , G06T2207/10048
摘要： Generating edge-depth values for an object, utilizing the edge-depth values in generating a 3D point cloud for the object, and utilizing the generated 3D point cloud for generating a 3D bounding shape (e.g., 3D bounding box) for the object. Edge-depth values for an object are depth values that are determined from frame(s) of vision data (e.g., left/right images) that captures the object, and that are determined to correspond to an edge of the object (an edge from the perspective of frame(s) of vision data). Techniques that utilize edge-depth values for an object (exclusively, or in combination with other depth values for the object) in generating 3D bounding shapes can enable accurate 3D bounding shapes to be generated for partially or fully transparent objects. Such increased accuracy 3D bounding shapes directly improve performance of a robot that utilizes the 3D bounding shapes in performing various tasks.
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公开(公告)号：US11657282B2
公开(公告)日：2023-05-23
申请号：US16571760
申请日：2019-09-16
发明人： Jamie Menjay Lin , Yang Yang , Jilei Hou
CPC分类号： G06N3/0472 , G06F17/15 , G06F17/16 , G06K9/6262 , G06N3/04 , G06N3/08 , G06N3/084 , G06K9/6267 , G06T7/70 , G06T2207/20084 , G06V40/10
摘要： Embodiments described herein relate to a method, comprising: receiving input data at a convolutional neural network (CNN) model; generating a factorized computation network comprising a plurality of connections between a first layer of the CNN model and a second layer of the CNN model, wherein: the factorized computation network comprises N inputs, the factorized computation network comprises M outputs, and the factorized computation network comprises at least one path from every input of the N inputs to every output of the M outputs; setting a connection weight for a plurality of connections in the factorized computation network to 1 so that a weight density for the factorized computation network is
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公开(公告)号：US11652720B2
公开(公告)日：2023-05-16
申请号：US16578199
申请日：2019-09-20
发明人： Shandan Zhou , John Lawrence Miller , Christopher Cowdery , Thomas Moscibroda , Shanti Kemburu , Yong Xu , Si Qin , Qingwei Lin , Eli Cortez , Karthikeyan Subramanian
CPC分类号： G06F9/5011 , G06F8/60 , G06F9/5027 , G06F9/544 , G06K9/6256 , G06K9/6267 , G06N20/00
摘要： The present disclosure relates to systems, methods, and computer readable media for predicting deployment growth on one or more node clusters and selectively permitting deployment requests on a per cluster basis. For example, systems disclosed herein may apply tenant growth prediction system trained to output a deployment growth classification indicative of a predicted growth of deployments on a node cluster. The system disclosed herein may further utilize the deployment growth classification to determine whether a deployment request may be permitted while maintaining a sufficiently sized capacity buffer to avoid deployment failures for existing deployments previously implemented on the node cluster. By selectively permitting or denying deployments based on a variety of factors, the systems described herein can more efficiently utilize cluster resources on a per-cluster basis without causing a significant increase in deployment failures for existing customers.
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公开(公告)号：US11651749B2
公开(公告)日：2023-05-16
申请号：US17217469
申请日：2021-03-30
申请人： Panduit Corp.
CPC分类号： G09G5/14 , G06F3/14 , G06K9/6267 , G09G5/38 , G06V2201/10 , G09G2320/0613 , G09G2340/0442 , G09G2340/0464 , G09G2370/20
摘要： A system and method for optimizing a display layout of multiple video streams at a sink device is provided. The display layout of multiple streams may be dynamically optimized based on a number of different variables, including characteristics of the sink device, total number of active incoming streams, active audio, and other characteristics of the source material or device. The source of an incoming media stream may contain useful characteristics for optimizing the display layout of multiple media streams. One such characteristic of a source device may include the device type, such as laptop, PC, phone, or tablet. Information may be extracted from each incoming stream in order to predict a source device type from which the incoming media stream originates.
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