公开(公告)号：US11875239B2

公开(公告)日：2024-01-16

申请号：US18103328

申请日：2023-01-30

申请人： FAIR ISAAC CORPORATION

发明人： Chong Huang ,  Arash Nourian ,  Feier Lian ,  Longfei Fan ,  Kevin Griest ,  Jari Koister ,  Andrew Flint

IPC分类号： G06N20/00 ,  G06F17/18 ,  G06V10/70 ,  G06F18/10 ,  G06F18/21 ,  G06F18/25

CPC分类号： G06N20/00 ,  G06F17/18 ,  G06F18/10 ,  G06F18/217 ,  G06F18/251 ,  G06V10/70

摘要： Computer-implemented machines, systems and methods for managing missing values in a dataset for a machine learning model. The method may comprise importing a dataset with missing values; computing data statistics and identifying the missing values; verifying the missing values; updating the missing values; imputing missing values; encoding reasons for why values are missing; combining imputed missing values and the encoded reasons; and recommending models and hyperparameters to handle special or missing values.

公开(公告)号：US11853377B2

公开(公告)日：2023-12-26

申请号：US14916720

申请日：2014-09-26

申请人： SEE-OUT PTY LTD

发明人： Sandra Mau

IPC分类号： G06F16/9538 ,  G06F16/951 ,  G06F16/51 ,  G06F16/248 ,  G06F16/22 ,  G06F16/2457 ,  G06T7/90 ,  G06T7/11 ,  G06F16/583 ,  G06F16/58 ,  G06F18/10 ,  G06F18/21 ,  G06T3/40 ,  G06T5/00 ,  G06V30/10

CPC分类号： G06F16/9538 ,  G06F16/2228 ,  G06F16/248 ,  G06F16/24578 ,  G06F16/51 ,  G06F16/58 ,  G06F16/583 ,  G06F16/5838 ,  G06F16/5846 ,  G06F16/5854 ,  G06F16/951 ,  G06F18/10 ,  G06F18/2178 ,  G06T3/40 ,  G06T5/002 ,  G06T7/11 ,  G06T7/90 ,  G06V30/10 ,  G06V2201/09 ,  G06V2201/10

摘要： Apparatus for performing searching of a plurality of reference images, the apparatus including one or more electronic processing devices that search the plurality of reference images to identify first reference images similar to a sample image, identify image tags associated with at least one of the first reference image, search the plurality of reference images to identify second reference images using at least one of the image tags and provide search results including at least some first and second reference images.

公开(公告)号：US11793575B2

公开(公告)日：2023-10-24

申请号：US17322193

申请日：2021-05-17

申请人： HeartFlow, Inc.

发明人： Charles A. Taylor

IPC分类号： G06T7/11 ,  A61B34/10 ,  G06F17/10 ,  A61B34/00 ,  G16B5/00 ,  G16B45/00 ,  G06T7/70 ,  G06T7/73 ,  G06T7/12 ,  G06T7/13 ,  G06T7/149 ,  G06T7/62 ,  A61B5/02 ,  A61B6/00 ,  G16H10/60 ,  G16H50/30 ,  G16H50/50 ,  G06F30/20 ,  G06F30/23 ,  G16H70/00 ,  G06V20/69 ,  G06F18/10 ,  G06F18/22 ,  G06F18/24 ,  G06V10/42 ,  G06V10/40 ,  G06V10/44 ,  G06F30/28 ,  A61B5/026 ,  G06G7/60 ,  A61B5/00 ,  A61B5/029 ,  A61B6/03 ,  A61B8/06 ,  A61B8/08 ,  G01R33/563 ,  A61B5/107 ,  G06T7/00 ,  G06T17/00 ,  A61B5/021 ,  A61B5/024 ,  A61B5/22 ,  G06T7/20 ,  G06T11/00 ,  G06T11/20 ,  A61M5/00 ,  A61B5/055 ,  A61B5/11 ,  G06T17/20 ,  G06T15/10 ,  G06T11/60 ,  G06T7/60 ,  A61B8/02 ,  A61B8/04 ,  G01R33/56 ,  G16H30/20 ,  G16H30/40 ,  G16H10/40 ,  G16H50/70 ,  A61B90/00 ,  G06T7/10 ,  G06V10/46

CPC分类号： A61B34/10 ,  A61B5/004 ,  A61B5/0035 ,  A61B5/0044 ,  A61B5/02 ,  A61B5/021 ,  A61B5/024 ,  A61B5/026 ,  A61B5/02007 ,  A61B5/029 ,  A61B5/02028 ,  A61B5/0263 ,  A61B5/055 ,  A61B5/1075 ,  A61B5/1118 ,  A61B5/22 ,  A61B5/4848 ,  A61B5/6852 ,  A61B5/7246 ,  A61B5/7275 ,  A61B5/7278 ,  A61B5/745 ,  A61B6/03 ,  A61B6/032 ,  A61B6/481 ,  A61B6/503 ,  A61B6/504 ,  A61B6/507 ,  A61B6/5205 ,  A61B6/5217 ,  A61B6/5229 ,  A61B8/02 ,  A61B8/04 ,  A61B8/06 ,  A61B8/065 ,  A61B8/481 ,  A61B8/5223 ,  A61B8/5261 ,  A61B34/25 ,  A61M5/007 ,  G01R33/5601 ,  G01R33/5635 ,  G01R33/56366 ,  G06F17/10 ,  G06F18/10 ,  G06F18/22 ,  G06F18/24 ,  G06F30/20 ,  G06F30/23 ,  G06F30/28 ,  G06G7/60 ,  G06T7/0012 ,  G06T7/0014 ,  G06T7/11 ,  G06T7/12 ,  G06T7/13 ,  G06T7/149 ,  G06T7/20 ,  G06T7/60 ,  G06T7/62 ,  G06T7/70 ,  G06T7/73 ,  G06T7/74 ,  G06T11/00 ,  G06T11/001 ,  G06T11/008 ,  G06T11/20 ,  G06T11/60 ,  G06T15/10 ,  G06T17/00 ,  G06T17/005 ,  G06T17/20 ,  G06V10/40 ,  G06V10/42 ,  G06V10/44 ,  G06V20/698 ,  G16B5/00 ,  G16B45/00 ,  G16H10/40 ,  G16H10/60 ,  G16H30/20 ,  G16H30/40 ,  G16H50/30 ,  G16H50/50 ,  G16H50/70 ,  G16H70/00 ,  A61B5/6868 ,  A61B2034/104 ,  A61B2034/105 ,  A61B2034/107 ,  A61B2034/108 ,  A61B2090/374 ,  A61B2090/3762 ,  A61B2090/3764 ,  A61B2576/00 ,  A61B2576/023 ,  G06T7/10 ,  G06T2200/04 ,  G06T2207/10012 ,  G06T2207/10072 ,  G06T2207/10081 ,  G06T2207/10088 ,  G06T2207/10104 ,  G06T2207/10108 ,  G06T2207/20036 ,  G06T2207/20124 ,  G06T2207/30016 ,  G06T2207/30048 ,  G06T2207/30104 ,  G06T2210/41 ,  G06T2211/404 ,  G06V10/467 ,  Y02A90/10 ,  G06T7/0012 ,  G06T2207/30048

摘要： Embodiments include a system for determining cardiovascular information for a patient. The system may include at least one computer system configured to receive patient-specific data regarding a geometry of the patient's heart, and create a three-dimensional model representing at least a portion of the patient's heart based on the patient-specific data. The at least one computer system may be further configured to create a physics-based model relating to a blood flow characteristic of the patient's heart and determine a fractional flow reserve within the patient's heart based on the three-dimensional model and the physics-based model.

公开(公告)号：US20230260360A1

公开(公告)日：2023-08-17

申请号：US18138514

申请日：2023-04-24

申请人： ARB LABS INC.

发明人： Adrian BULZACKI ,  Vlad CAZAN

IPC分类号： G07F17/32 ,  A63F3/00 ,  G06V10/10 ,  G06V10/25 ,  G06V10/141 ,  G06V20/52 ,  G06V20/64 ,  G06V20/80 ,  G06V10/74 ,  G06T7/50 ,  G06F18/10 ,  G06V10/20 ,  G06V10/50 ,  G06V10/147 ,  G06V10/75 ,  G06V10/26 ,  G06V10/22

CPC分类号： G07F17/3227 ,  A63F3/00157 ,  G06V10/10 ,  G06V10/25 ,  G06V10/141 ,  G06V20/52 ,  G06V20/64 ,  G06V20/80 ,  G06V10/74 ,  G07F17/3248 ,  G06T7/50 ,  G07F17/3237 ,  G07F17/3241 ,  G06F18/10 ,  G06V10/20 ,  G06V10/50 ,  G06V10/147 ,  G06V10/758 ,  G06V10/273 ,  G06V10/26 ,  G06V10/22 ,  G07F17/3211 ,  G07F17/322 ,  A63F2003/00164 ,  G06V10/40

摘要： System, processes and devices for monitoring betting activities using bet recognition devices and a server. Each bet recognition device has an imaging component for capturing image data for a gaming table surface. The bet recognition device receives calibration data for calibrating the bet recognition device. A server processor coupled to a data store processes the image data received from the bet recognition devices over the network to detect, for each betting area, a number of chips and a final bet value for the chips.

公开(公告)号：US11715333B2

公开(公告)日：2023-08-01

申请号：US17735959

申请日：2022-05-03

申请人： FotoNation Limited

发明人： Florin Nanu ,  Stefan Petrescu ,  Florin Oprea ,  Emanuela Haller

IPC分类号： G06V40/18 ,  G06T7/50 ,  G06V20/59 ,  G06F18/10 ,  G06T7/70 ,  H04N23/56

CPC分类号： G06V40/193 ,  G06F18/10 ,  G06T7/50 ,  G06T7/70 ,  G06V20/597 ,  G06V40/18 ,  G06T2207/10016 ,  G06T2207/10048 ,  G06T2207/30201 ,  G06T2207/30268 ,  H04N23/56

摘要： Related methods are provided for establishing a baseline value to represent an eyelid opening dimension for a person engaged in an activity, where the activity may be driving a vehicle, operating industrial equipment, or performing a monitoring or control function; and for operating a system for monitoring eyelid opening values with real time video data.

公开(公告)号：US11693624B2

公开(公告)日：2023-07-04

申请号：US16911490

申请日：2020-06-25

申请人： Beijing Baidu Netcom Science Technology Co., Ltd.

发明人： Xintong Mou ,  Long Wang ,  Hao Li ,  Kuan Shi ,  Bo Peng ,  Haitao Yu ,  Qianqian Sha ,  Wenbin Ren ,  Xianyuan Mo ,  Haobo Wu

IPC分类号： G06F16/903 ,  G06F7/24 ,  G06N20/00 ,  G06F17/18 ,  G06F18/40 ,  G06F18/10 ,  G06F18/211

CPC分类号： G06F7/24 ,  G06F16/903 ,  G06F17/18 ,  G06F18/10 ,  G06F18/211 ,  G06F18/40 ,  G06N20/00

摘要： Embodiments of the present disclosure provide an AI capability research and development platform and a data processing method. The AI capability research and development platform includes: a data management module, a tool management module, a process management module and a model management module, where the data management module is configured to perform data processing on received data, including at least one of the following: analyzing data type of the data, converting the data according to preset data format and storing the data; the tool management module is configured to store at least one tool, each tool being used to execute a preset processing flow; the process management module is configured to perform model training according to the tool provided by the tool management module and the data provided by the data management module; the model management module is configured to store a model obtained by the model training.

公开(公告)号：US11690586B2

公开(公告)日：2023-07-04

申请号：US18149021

申请日：2022-12-30

申请人： CLEERLY, INC.

发明人： James K. Min ,  James P. Earls ,  Hugo Miguel Rodrigues Marques ,  Ben Hootnick

IPC分类号： G06K9/00 ,  A61B6/00 ,  A61B8/14 ,  A61B6/03 ,  A61B5/00 ,  G06T7/00 ,  A61B8/12 ,  A61B5/055 ,  A61K49/04 ,  A61B5/02 ,  G06F18/10 ,  G06V10/74 ,  G06V10/764 ,  G06V10/20 ,  G06V10/24 ,  G06V40/14

CPC分类号： A61B6/481 ,  A61B5/0066 ,  A61B5/0075 ,  A61B5/02007 ,  A61B5/055 ,  A61B5/7267 ,  A61B5/742 ,  A61B5/7475 ,  A61B6/032 ,  A61B6/037 ,  A61B6/504 ,  A61B6/5205 ,  A61B6/5217 ,  A61B8/12 ,  A61B8/14 ,  A61K49/04 ,  G06F18/10 ,  G06T7/0012 ,  G06V10/20 ,  G06V10/245 ,  G06V10/761 ,  G06V10/764 ,  G06V40/14 ,  G06T2207/10081 ,  G06T2207/10088 ,  G06T2207/10101 ,  G06T2207/10132 ,  G06T2207/20081 ,  G06T2207/30048 ,  G06T2207/30101 ,  G06V10/247

摘要： The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

公开(公告)号：US20230177826A1

公开(公告)日：2023-06-08

申请号：US18163482

申请日：2023-02-02

申请人： Nvidia Corporation

发明人： Aayush Prakash ,  Shoubhik Debnath ,  Jean-Francois Lafleche ,  Eric Cameracci ,  Gavriel State ,  Marc Teva Law

IPC分类号： G06V10/82 ,  G06V20/70 ,  G06F18/10 ,  G06F18/24 ,  G06F18/20 ,  G06V10/764 ,  G06V10/84 ,  G06V20/00

CPC分类号： G06V10/82 ,  G06V20/70 ,  G06F18/10 ,  G06F18/24 ,  G06F18/29 ,  G06V10/764 ,  G06V10/84 ,  G06V20/00 ,  G06V20/56

摘要： Approaches are presented for training and using scene graph generators for transfer learning. A scene graph generation technique can decompose a domain gap into individual types of discrepancies, such as may relate to appearance, label, and prediction discrepancies. These discrepancies can be reduced, at least in part, by aligning the corresponding latent and output distributions using one or more gradient reversal layers (GRLs). Label discrepancies can be addressed using self-pseudo-statistics collected from target data. Pseudo statistic-based self-learning and adversarial techniques can be used to manage these discrepancies without the need for costly supervision from a real-world dataset.

公开(公告)号：US20230144293A1

公开(公告)日：2023-05-11

申请号：US18148697

申请日：2022-12-30

申请人： CLEERLY, INC.

发明人： James K. MIN ,  James P. EARLS ,  Hugo Miguel RODRIGUES MARQUES

IPC分类号： A61B6/00 ,  G06T7/00 ,  A61B5/055 ,  A61B6/03 ,  A61B8/14 ,  A61B8/12 ,  A61B5/00 ,  A61K49/04 ,  G06F18/10 ,  G06V10/74 ,  G06V10/764 ,  G06V10/82 ,  G06V10/20 ,  G06V10/24

CPC分类号： A61B6/504 ,  G06T7/0012 ,  A61B5/055 ,  A61B6/032 ,  A61B6/037 ,  A61B8/14 ,  A61B8/12 ,  A61B5/0075 ,  A61B6/481 ,  A61B6/5205 ,  A61B5/0066 ,  A61B5/742 ,  A61B5/7475 ,  A61K49/04 ,  A61B5/7267 ,  G06F18/10 ,  G06V10/761 ,  G06V10/764 ,  G06V10/82 ,  G06V10/20 ,  G06V10/245 ,  G06T2207/30048 ,  G06T2207/10081 ,  G06T2207/10088 ,  G06T2207/10101 ,  G06T2207/10132 ,  G06T2207/20081 ,  G06T2207/30101 ,  G06V10/247

摘要： The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

公开(公告)号：US20240320303A1

公开(公告)日：2024-09-26

申请号：US18680987

申请日：2024-05-31

申请人： Oracle International Corporation

发明人： Alberto Polleri ,  Sergio Aldea Lopez ,  Marc Michiel Bron ,  Dan David Golding ,  Alexander Ioannides ,  Maria Del Rosario Mestre ,  Hugo Alexandre Pereira Monteiro ,  Oleg Gennadievich Shevelev ,  Larissa Cristina Dos Santos Romualdo Suzuki ,  Xiaoxue Zhao ,  Matthew Charles Rowe

IPC分类号： G06F18/213 ,  G06F8/75 ,  G06F8/77 ,  G06F11/30 ,  G06F11/34 ,  G06F16/21 ,  G06F16/23 ,  G06F16/2457 ,  G06F16/28 ,  G06F16/36 ,  G06F16/901 ,  G06F16/9035 ,  G06F16/907 ,  G06F18/10 ,  G06F18/2115 ,  G06F18/214 ,  G06N5/01 ,  G06N5/025 ,  G06N20/00 ,  G06N20/20 ,  H04L9/08 ,  H04L9/32

CPC分类号： G06F18/213 ,  G06F8/75 ,  G06F8/77 ,  G06F11/3003 ,  G06F11/3409 ,  G06F11/3433 ,  G06F11/3452 ,  G06F11/3466 ,  G06F16/211 ,  G06F16/2365 ,  G06F16/24573 ,  G06F16/24578 ,  G06F16/285 ,  G06F16/367 ,  G06F16/9024 ,  G06F16/9035 ,  G06F16/907 ,  G06F18/10 ,  G06F18/2115 ,  G06F18/2155 ,  G06N5/01 ,  G06N5/025 ,  G06N20/00 ,  G06N20/20 ,  H04L9/088 ,  H04L9/0894 ,  H04L9/3236

摘要： A server system may receive two or more Quality of Service (QoS) dimensions for the multi-objective optimization model, wherein the two or more QoS dimensions include at least a first QoS dimension and a second QoS dimension. The server system may maximize the multi-objective optimization model along the first QoS dimension, wherein the maximizing includes selecting one or more pipelines for the multi-objective optimization model in the software architecture that meet QoS expectations specified for the first QoS dimension and the second QoS dimension, wherein an ordering of the pipelines is dependent on which QoS dimensions were optimized and de-optimized and to what extent, wherein the multi-objective optimization model is partially de-optimized along the second QoS dimension in order to comply with the QoS expectations for the first QoS dimension, and whereby there is a tradeoff between the first QoS dimension and the second QoS dimension.