公开(公告)号：US12132953B2

公开(公告)日：2024-10-29

申请号：US17401656

申请日：2021-08-13

申请人： Gracenote, Inc.

发明人： Amanmeet Garg ,  Sharmishtha Gupta ,  Andreas Schmidt ,  Lakshika Balasuriya ,  Aneesh Vartakavi

IPC分类号： H04N21/44 ,  G06F18/25 ,  G06V20/40 ,  H04N21/8352

CPC分类号： H04N21/44008 ,  G06F18/253 ,  G06V20/41 ,  H04N21/8352

摘要： In one aspect, an example method includes (i) obtaining fingerprint repetition data for a portion of video content, with the fingerprint repetition data including a list of other portions of video content matching the portion of video content and respective reference identifiers for the other portions of video content; (ii) identifying the portion of video content as a program segment rather than an advertisement segment based at least on a number of unique reference identifiers within the list of other portions of video content relative to a total number of reference identifiers within the list of other portions of video content; (iii) determining that the portion of video content corresponds to a program specified in an electronic program guide using a timestamp of the portion of video content; and (iv) storing an indication of the portion of video content in a data file for the program.

公开(公告)号：US12125146B1

公开(公告)日：2024-10-22

申请号：US17575091

申请日：2022-01-13

申请人： GridRaster, Inc.

发明人： Yiyong Tan ,  Bhaskar Banerjee ,  Rishi Ranjan

IPC分类号： G06T19/00 ,  G06F18/25 ,  G06N3/045 ,  G06N5/04 ,  G06N20/10

CPC分类号： G06T19/006 ,  G06F18/25 ,  G06N3/045 ,  G06N5/04 ,  G06N20/10

摘要： A mixed reality (MR) system and method performs three dimensional (3D) tracking using 3D deep neural network structures in which multimodal fusion and simplified machine learning to only cluster label distribution (output of 3D deep neural network trained by generic 3D benchmark dataset) is used to reduce the training data requirements of to directly train a 3D deep neural network structures for non-generic user case. In one embodiment, multiple 3D deep neural network structures, such as PointCNN, 3D-Bonet, RandLA, etc., may be trained by different generic 3D benchmark datasets, such as ScanNet, ShapeNet, S3DIS, inadequate 3D training dataset, etc.

公开(公告)号：US12112455B2

公开(公告)日：2024-10-08

申请号：US17202731

申请日：2021-03-16

申请人： Vinai Artificial Intelligence Application and Research Joint Stock Company

发明人： Hung Hai Bui ,  Hoai Minh Nguyen ,  Phong The Tran ,  Anh Tuan Tran ,  Thao Phuong Nguyen Thi

IPC分类号： G06T5/70 ,  G06F18/25 ,  G06T5/50 ,  G06V10/44 ,  G06V40/16

CPC分类号： G06T5/70 ,  G06F18/253 ,  G06T5/50 ,  G06V10/44 ,  G06V40/169

摘要： Provided is a Face-aware Offset Calculation (FOC) module and method for facial frame interpolation and enhancement and a face video deblurring system and method using the same. The system comprises: a facial frame enhancement device, including a FOC module, for enhancing a target frame; a facial frame interpolation device, including the FOC module, for interpolating the target frame; and a combination device for combining the enhanced target frame with the interpolated target frame.

公开(公告)号：US12106235B2

公开(公告)日：2024-10-01

申请号：US16360480

申请日：2019-03-21

申请人： United Technologies Corporation

发明人： Sharath B. Nagaraja ,  Mathew R. Greco

IPC分类号： G06Q10/04 ,  B64F5/60 ,  G05B23/02 ,  G06F18/25 ,  G06N3/04 ,  G08G5/00 ,  H04W4/029

CPC分类号： G06Q10/04 ,  B64F5/60 ,  G05B23/0281 ,  G05B23/0283 ,  G06F18/25 ,  G06N3/04 ,  G08G5/0026 ,  G08G5/0039 ,  G08G5/006 ,  H04W4/029

摘要： A method for forecasting aircraft engine deterioration includes creating a first fused data set corresponding to a first actual aircraft engine. The first fused data set includes at least one as manufactured parameter of the actual aircraft engine, expected operating parameters of the first actual aircraft engine, and actual operating parameters of the actual aircraft engine. The actual operating parameters of the actual aircraft engine include internal aircraft sensor data, and external flight tracking data. The method further includes predicting an expected engine deterioration of the first actual engine based on the expected operating parameters and the actual operating parameters of the first actual aircraft engine by applying the first fused data set to a forecasting model. The forecasting model is a recurrent neural network based algorithm, and the recurrent neural network based algorithm is trained via a plurality of second fused data sets corresponding to actual aircraft engines.

公开(公告)号：US12105775B2

公开(公告)日：2024-10-01

申请号：US17484077

申请日：2021-09-24

申请人： Haier US Appliance Solutions, Inc.

发明人： Michael Goodman Schroeder

IPC分类号： G06F18/25 ,  F25D29/00 ,  G06N3/08 ,  G06V20/40 ,  G06V20/52 ,  G06V20/68 ,  G10L15/22 ,  G10L15/26 ,  G10L25/51

CPC分类号： G06F18/25 ,  F25D29/00 ,  G06N3/08 ,  G06V20/40 ,  G06V20/52 ,  G10L15/22 ,  G10L15/26 ,  G10L25/51 ,  F25D2500/06 ,  F25D2700/06 ,  G06V20/68

摘要： A refrigerator appliance is provided including a cabinet defining a chilled chamber, a door rotatably hinged to the cabinet to provide selective access to the chilled chamber, and an audiovisual input assembly for monitoring the chilled chamber. A controller obtains a video stream and an audio stream using the audiovisual input assembly and analyzes these streams using a standard object weighting to generate a video-based inventory change and an audio-based inventory change. An inventory list is updated if the video-based inventory change and the audio-based inventory change match. Otherwise, the controller can reanalyze the streams using an updated object weighting to see if the audio and video streams generate matching proposed inventory changes.

公开(公告)号：US12105770B2

公开(公告)日：2024-10-01

申请号：US17191771

申请日：2021-03-04

申请人： KABUSHIKI KAISHA TOSHIBA

发明人： Norihiro Nakamura ,  Akihito Seki

IPC分类号： G06F18/211 ,  G06F18/214 ,  G06F18/25 ,  G06N3/08 ,  G06T15/00 ,  G01S17/66

CPC分类号： G06F18/211 ,  G06F18/214 ,  G06F18/251 ,  G06N3/08 ,  G06T15/00 ,  G01S17/66 ,  G06T2210/52

摘要： According to an embodiment, an estimation device includes one or more processors configured to: generate, from first point cloud data, second point cloud data obtained by combining an attention point and observation points; estimate an attribute of the attention point by an attribute indicated by an estimation result label having a higher belonging probability among belonging probabilities output from an attribute estimation neural network; estimate reliability of the estimation result label by a reliability estimation neural network; and display, on a display device, first display information generated by performing rendering on an object including an attention point whose attribute is estimated by an attribute of the estimation result label whose reliability is higher than a first threshold, and generated by not performing rendering on an object including an attention point whose attribute is estimated by an attribute of the estimation result label whose reliability is the first threshold or less.

公开(公告)号：US20240315654A1

公开(公告)日：2024-09-26

申请号：US18590033

申请日：2024-02-28

申请人： Hologic, Inc.

发明人： Haili CHUI ,  Liyang WEI ,  Jun GE ,  Xiangwei ZHANG ,  Nikolaos GKANATSIOS

IPC分类号： A61B6/50 ,  A61B6/02 ,  G06F18/25 ,  G06T7/00 ,  G06T17/10 ,  G06V10/80 ,  G06V30/24

CPC分类号： A61B6/502 ,  A61B6/025 ,  G06F18/254 ,  G06T7/0012 ,  G06T17/10 ,  G06V10/806 ,  G06V10/809 ,  G06V30/2504 ,  G06T2207/30068

摘要： A method for processing breast tissue image data includes processing the image data to generate a set of image slices collectively depicting the patient's breast; for each image slice, applying one or more filters associated with a plurality of multi-level feature modules, each configured to represent and recognize an assigned characteristic or feature of a high-dimensional object; generating at each multi-level feature module a feature map depicting regions of the image slice having the assigned feature; combining the feature maps generated from the plurality of multi-level feature modules into a combined image object map indicating a probability that the high-dimensional object is present at a particular location of the image slice; and creating a 2D synthesized image identifying one or more high-dimensional objects based at least in part on object maps generated for a plurality of image slices.

公开(公告)号：US12099911B2

公开(公告)日：2024-09-24

申请号：US18076494

申请日：2022-12-07

申请人： Strong Force IoT Portfolio 2016, LLC

发明人： Charles Howard Cella ,  Gerald William Duffy, Jr. ,  Jeffrey P. McGuckin ,  Mehul Desai

IPC分类号： G06N3/006 ,  B62D15/02 ,  G01M13/028 ,  G01M13/04 ,  G01M13/045 ,  G05B13/02 ,  G05B19/418 ,  G05B23/02 ,  G06F18/21 ,  G06N3/02 ,  G06N3/044 ,  G06N3/045 ,  G06N3/047 ,  G06N3/084 ,  G06N3/088 ,  G06N5/046 ,  G06N7/01 ,  G06N20/00 ,  G06Q10/04 ,  G06Q10/0639 ,  G06Q30/02 ,  G06Q30/06 ,  G06Q50/00 ,  G06V10/778 ,  G06V10/82 ,  G16Z99/00 ,  H02M1/12 ,  H03M1/12 ,  H04B17/23 ,  H04B17/309 ,  H04B17/318 ,  H04B17/345 ,  H04L1/00 ,  H04L1/18 ,  H04L1/1867 ,  H04L67/1097 ,  H04L67/12 ,  H04W4/38 ,  H04W4/70 ,  B62D5/04 ,  G05B19/042 ,  G06F17/18 ,  G06F18/25 ,  G06N3/126 ,  H01B17/40 ,  H04B17/29 ,  H04B17/40 ,  H04L5/00 ,  H04L67/306

CPC分类号： G06N3/006 ,  B62D15/0215 ,  G01M13/028 ,  G01M13/04 ,  G01M13/045 ,  G05B13/028 ,  G05B19/4183 ,  G05B19/4184 ,  G05B19/41845 ,  G05B19/4185 ,  G05B19/41865 ,  G05B19/41875 ,  G05B23/0221 ,  G05B23/0229 ,  G05B23/024 ,  G05B23/0264 ,  G05B23/0283 ,  G05B23/0286 ,  G05B23/0289 ,  G05B23/0291 ,  G05B23/0294 ,  G05B23/0297 ,  G06F18/2178 ,  G06N3/02 ,  G06N3/044 ,  G06N3/045 ,  G06N3/047 ,  G06N3/084 ,  G06N3/088 ,  G06N5/046 ,  G06N7/01 ,  G06N20/00 ,  G06Q10/04 ,  G06Q10/0639 ,  G06Q30/02 ,  G06Q30/0278 ,  G06Q30/06 ,  G06Q50/00 ,  G06V10/7784 ,  G06V10/82 ,  G16Z99/00 ,  H02M1/12 ,  H03M1/12 ,  H04B17/23 ,  H04B17/309 ,  H04B17/318 ,  H04B17/345 ,  H04L1/0002 ,  H04L1/0041 ,  H04L1/18 ,  H04L1/1874 ,  H04L67/1097 ,  H04L67/12 ,  H04W4/38 ,  H04W4/70 ,  B62D5/0463 ,  G05B19/042 ,  G05B23/02 ,  G05B23/0208 ,  G05B2219/32287 ,  G05B2219/35001 ,  G05B2219/37337 ,  G05B2219/37351 ,  G05B2219/37434 ,  G05B2219/37537 ,  G05B2219/40115 ,  G05B2219/45004 ,  G05B2219/45129 ,  G06F17/18 ,  G06F18/21 ,  G06F18/217 ,  G06F18/25 ,  G06N3/126 ,  H01B17/40 ,  H04B17/29 ,  H04B17/40 ,  H04L1/0009 ,  H04L5/0064 ,  H04L67/306 ,  Y02P80/10 ,  Y02P90/02 ,  Y02P90/80 ,  Y04S50/00 ,  Y04S50/12 ,  Y10S707/99939

摘要： System and methods for learning data patterns predictive of an outcome are described. An example system may include a plurality of input sensors communicatively coupled to a controller; a data collection circuit structured to collect output data from the plurality of input sensors; and a machine learning data analysis circuit structured to receive the output data, learn received output data patterns indicative of an outcome, and learn a preferred input data collection band among a plurality of available input data collection bands. The machine learning data analysis circuit may be structured to learn received output data patterns by being seeded with a model based on industry-specific feedback. The outcome may be at least one of: a reaction rate, a production volume, or a required maintenance.

公开(公告)号：US12080072B2

公开(公告)日：2024-09-03

申请号：US17308908

申请日：2021-05-05

申请人： Aptiv Technologies AG

发明人： Syed Asif Imran ,  Jan K. Schiffmann ,  Nianxia Cao

IPC分类号： G06V20/56 ,  G01C21/20 ,  G01S13/72 ,  G01S13/86 ,  G01S13/931 ,  G01S17/86 ,  G01S17/931 ,  G06F18/25 ,  G08G1/16

CPC分类号： G06V20/56 ,  G06F18/251 ,  G08G1/166

摘要： This document describes methods and systems directed at history-based identification of incompatible tracks. The historical trajectory of tracks can be advantageous to accurately determine whether tracks originating from different sensors identify the same object or different objects. However, recording historical data of several tracks may consume vast amounts of memory or computing resources, and related computations may become complex. The methods and systems described herein enable a sensor fusion system of an automobile or other vehicle to consider historical data when associating and pairing tracks, without requiring large amounts of memory and without tying up other computing resources.

公开(公告)号：US20240288872A1

公开(公告)日：2024-08-29

申请号：US18531887

申请日：2023-12-07

申请人： JAR Scientific, LLC

发明人： Justin Starr ,  Ashish Basuray ,  Roman Kazantsev

IPC分类号： G05D1/00 ,  B60L58/12 ,  B64C39/02 ,  B64D1/16 ,  B64D9/00 ,  B64D47/08 ,  B64F1/36 ,  B64U10/13 ,  B64U50/19 ,  B64U101/30 ,  G01S19/45 ,  G05D1/249 ,  G05D1/692 ,  G05D1/698 ,  G06F18/25 ,  G06V10/764 ,  G06V10/82 ,  G06V20/10 ,  G06V20/13 ,  G06V20/17 ,  G06V20/52 ,  G06V40/10 ,  G08G5/00 ,  G08G5/02 ,  G08G5/04

CPC分类号： G05D1/104 ,  B60L58/12 ,  B64C39/024 ,  B64D1/16 ,  B64D9/00 ,  B64D47/08 ,  B64F1/362 ,  G01S19/45 ,  G05D1/249 ,  G05D1/692 ,  G05D1/698 ,  G06F18/25 ,  G06V10/764 ,  G06V10/82 ,  G06V20/10 ,  G06V20/13 ,  G06V20/17 ,  G06V20/176 ,  G06V20/52 ,  G08G5/0043 ,  G08G5/02 ,  G08G5/045 ,  B60L2200/10 ,  B64U10/13 ,  B64U50/19 ,  B64U2101/30 ,  B64U2201/10 ,  G06V40/10 ,  G06V2201/08

摘要： An embodiment provides unmanned aerial vehicles (UAVs) for infrastructure surveillance and monitoring. One example includes monitoring power grid components such as high voltage power lines. The UAVs may coordinate, for example using swarm behavior, and be controlled via a platform system. Other embodiments are described and claimed.