公开(公告)号：US12079311B2

公开(公告)日：2024-09-03

申请号：US17145123

申请日：2021-01-08

Applicant: Salesforce, Inc.

Inventor： Carlos Andres Esteva ,  Douwe Stefan van der Wal

IPC: G06T7/11 ,  G06F18/214 ,  G06F18/2413 ,  G06F18/40 ,  G06N3/08 ,  G06T7/00 ,  G06V10/25 ,  G06V10/40

CPC classification number: G06F18/2413 ,  G06F18/214 ,  G06F18/40 ,  G06N3/08 ,  G06T7/0012 ,  G06T7/11 ,  G06V10/25 ,  G06V10/40 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30024 ,  G06V2201/03

Abstract: An AI-enhanced data labeling tool assists a human operator in annotating image data. The tool may use a segmentation model to identify portions to be labeled. Initially, the operator manually annotates portions and once the operator has labeled a sufficient number of portions, a classifier is trained to predict labels for other portions. The predictions generated by the classifier are presented to the operator for approval or modification. The tool may also include an active learning model that recommends portions of the image data for the operator to annotate next. The active learning model may suggest one or more batches of portions based on the extent to which, once labeled, those batches will increase the diversity of the total set of labeled portions.

公开(公告)号：US12056216B2

公开(公告)日：2024-08-06

申请号：US17801849

申请日：2020-03-19

Applicant: NEC Corporation

Inventor： Azusa Sawada ,  Takashi Shibata ,  Kazuto Takizawa

IPC: G06F18/40 ,  G01S13/90 ,  G06F18/21 ,  G06F18/214 ,  G06T3/40

CPC classification number: G06F18/40 ,  G01S13/9021 ,  G06F18/214 ,  G06F18/2163 ,  G06T3/40

Abstract: An image processing apparatus according to the present invention includes: an extracting unit configured to extract a candidate image, which is an image of a candidate region specified in accordance with a preset criterion, from a target image to be a target for an annotation process, and also extract a corresponding image, which is an image of a corresponding region corresponding to the candidate region, from a reference image that is an image corresponding to the target image; a displaying unit configured to display the candidate image and the corresponding image so as to be able to compare the images with each other; and an input accepting unit configured to accept input of input information for the annotation process for the candidate image.

公开(公告)号：US12039712B2

公开(公告)日：2024-07-16

申请号：US17186957

申请日：2021-02-26

Applicant: RedZone Robotics, Inc.

Inventor： Justin Starr ,  Galin Konakchiev ,  Foster J Salotti ,  Mark Jordan ,  Nate Alford ,  Thorin Tobiassen ,  Todd Kueny ,  Jason Mizgorski

IPC: G06K9/00 ,  G01M3/38 ,  G06F18/214 ,  G06F18/24 ,  G06F18/40 ,  G06T7/00 ,  G06T7/73 ,  G06V10/764 ,  G06V10/82 ,  G01M3/00

CPC classification number: G06T7/0004 ,  G01M3/38 ,  G06F18/2148 ,  G06F18/24 ,  G06F18/40 ,  G06T7/73 ,  G06V10/764 ,  G06V10/82 ,  G01M3/005 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/20092 ,  G06T2207/30108 ,  G06T2207/30184 ,  G06V2201/10

Abstract: One aspect provides operating a mobile pipe inspection platform to obtain two or more types of sensor data for the interior of a pipe; analyzing, using a processor, the two or more types of sensor data using a trained model, where the trained model is trained using a dataset including training sensor data of pipe interiors; the analyzing including performing: identifying, using a processor, a pipe feature location using a first type of the two or more types of sensor data; and classifying, using a processor, an identified pipe feature using a second type of the two or more types of sensor data; and thereafter producing, using a processor, an output including an indication of the classified pipe feature. Other aspects are described and claimed.

公开(公告)号：US12038802B2

公开(公告)日：2024-07-16

申请号：US17070520

申请日：2020-10-14

Applicant: PDF Solutions, Inc.

Inventor： Tomonori Honda ,  Richard Burch ,  John Kibarian ,  Lin Lee Cheong ,  Qing Zhu ,  Vaishnavi Reddipalli ,  Kenneth Harris ,  Said Akar ,  Jeffrey D David ,  Michael Keleher ,  Brian Stine ,  Dennis Ciplickas

IPC: G06N20/00 ,  G06F11/07 ,  G06F18/211 ,  G06F18/241 ,  G06F18/40 ,  H01L21/02 ,  G06F3/0482 ,  G06N3/08 ,  G06N7/01

CPC classification number: G06F11/079 ,  G06F11/0736 ,  G06F11/0751 ,  G06F11/0778 ,  G06F18/211 ,  G06F18/241 ,  G06F18/40 ,  G06N20/00 ,  H01L21/02 ,  G06F3/0482 ,  G06N3/08 ,  G06N7/01

Abstract: Classifying wafers using Collaborative Learning. An initial wafer classification is determined by a rule-based model. A predicted wafer classification is determined by a machine learning model. Multiple users can manually review the classifications to confirm or modify, or to add user classifications. All of the classifications are input to the machine learning model to continuously update its scheme for detection and classification.

公开(公告)号：US20240225447A1

公开(公告)日：2024-07-11

申请号：US18509061

申请日：2023-11-14

Applicant: HOLOGIC, INC.

Inventor： Haili CHUI ,  Zhenxue JING

IPC: A61B5/00 ,  G06F18/21 ,  G06F18/214 ,  G06F18/40 ,  G06N3/04 ,  G06N3/08 ,  G06V10/774 ,  G06V10/82

CPC classification number: A61B5/0033 ,  G06F18/214 ,  G06F18/217 ,  G06F18/40 ,  G06N3/04 ,  G06N3/08 ,  G06V10/774 ,  G06V10/82 ,  G06V2201/03

Abstract: A method and system for creating a dynamic self-learning medical image network system, wherein the method includes receiving, from a first node initial user interaction data pertaining to one or more user interactions with the one or more initially obtained medical images; training a deep learning algorithm based at least in part on the initial user interaction data received from the node; and transmitting an instance of the trained deep learning algorithm to the first node and/or to one or more additional nodes, wherein at each respective node to which the instance of the trained deep learning algorithm is transmitted, the trained deep learning algorithm is applied to respective one or more subsequently obtained medical images in order to obtain a result.

公开(公告)号：US12020415B2

公开(公告)日：2024-06-25

申请号：US17855130

申请日：2022-06-30

Applicant: Instrumental, Inc.

Inventor： Samuel Bruce Weiss ,  Anna-Katrina Shedletsky ,  Simon Kozlov ,  Tilmann Bruckhaus ,  Shilpi Kumar ,  Isaac Sukin ,  Ian Theilacker ,  Brendan Green

IPC: G06T7/00 ,  G06F18/213 ,  G06F18/40 ,  G06V10/25 ,  G06V10/40 ,  G06V10/771

CPC classification number: G06T7/0004 ,  G06F18/213 ,  G06F18/40 ,  G06T7/001 ,  G06V10/25 ,  G06V10/40 ,  G06V10/771 ,  G06T2207/30116 ,  G06T2207/30164

Abstract: One variation of a method for monitoring manufacture of assembly units includes: receiving selection of a target location hypothesized by a user to contain an origin of a defect in assembly units of an assembly type; accessing a feature map linking non-visual manufacturing features to physical locations within the assembly type; for each assembly unit, accessing an inspection image of the assembly unit recorded by an optical inspection station during production of the assembly unit, projecting the target location onto the inspection image, detecting visual features proximal the target location within the inspection image, and aggregating non-visual manufacturing features associated with locations proximal the target location and representing manufacturing inputs into the assembly unit based on the feature map; and calculating correlations between visual and non-visual manufacturing features associated with locations proximal the target location and the defect for the set of assembly units.

公开(公告)号：US20240203158A1

公开(公告)日：2024-06-20

申请号：US17772537

申请日：2021-04-01

Applicant: BOE Technology Group Co., Ltd.

Inventor： Tingting WANG ,  Jingtao XU

IPC: G06V40/16 ,  G06F18/40 ,  G06T3/40 ,  G06T7/33 ,  G06T7/73

CPC classification number: G06V40/165 ,  G06F18/40 ,  G06T3/40 ,  G06T7/337 ,  G06T7/73 ,  G06V40/169 ,  G06T2207/30201

Abstract: A method and apparatus for detecting a face attribute, a computer-readable storage medium and an electronic device are provided. The method includes: extracting a face image from a candidate image; acquiring a target image block corresponding to at least one target part of the face image; and obtaining, for one of the at least one target part, target attribute information by performing attribute detection on the target image block corresponding to the target part using a pre-trained attribute detection model corresponding to the target part.

公开(公告)号：US12014814B2

公开(公告)日：2024-06-18

申请号：US16775180

申请日：2020-01-28

Applicant: GE Precision Healthcare LLC

Inventor： Katelyn Nye ,  Gopal Avinash ,  Pal Tegzes ,  Gireesha Rao

IPC: G16H30/40 ,  G06F18/20 ,  G06F18/21 ,  G06F18/40 ,  G06N5/02 ,  G06N20/00 ,  G06T7/00 ,  G16H50/50

CPC classification number: G16H30/40 ,  G06F18/217 ,  G06F18/285 ,  G06F18/40 ,  G06N5/02 ,  G06N20/00 ,  G06T7/0012 ,  G16H50/50 ,  G06T2207/10116 ,  G06V2201/03

Abstract: Methods and systems are provided for tuning a static model with multiple operating points to adjust model performance without retraining the model or triggering a new regulatory clearance. In one embodiment, a method comprises, responsive to a request to tune a model, obtaining a tuning dataset including a set of medical images, executing the model using the set of medical images as input to generate model tuning output, and determining, for each operating point of a set of operating points, a set of tuning metric values based on the tuning dataset and the model tuning output relative to each operating point. An operating point from the set of operating points may be selected based on each set of tuning metric values and, upon a request to analyze a subsequent medical image, a representation of a finding output from the static model executed at the selected operating point.

公开(公告)号：US12008081B2

公开(公告)日：2024-06-11

申请号：US17303086

申请日：2021-05-19

Applicant: International Business Machines Corporation

Inventor： Tian Tian Chai ,  Hong Bing Zhang ,  Kun Yan Yin ,  Miao Guo ,  Yu Luo ,  Yun Jing Zhao

IPC: G06F18/40 ,  G06F18/214 ,  G06N20/00 ,  G06T7/246 ,  G06T11/20 ,  G06V20/40 ,  G06V40/20

CPC classification number: G06F18/40 ,  G06F18/214 ,  G06T7/246 ,  G06T11/203 ,  G06V20/46 ,  G06V40/28 ,  G06N20/00 ,  G06T2207/10016 ,  G06T2207/20081 ,  G06T2207/20104

Abstract: A method, a computing system and a computer program product for collecting and labelling images includes capturing a video of an object with a camera. A movement trace of a pointer is recorded that outlines the object while capturing the video of the object. Further included is generating a labeled image based at least on the captured video of the object and the recorded movement trace of the pointer. The labeled image includes the object and a line that surrounds the object.

公开(公告)号：US11971955B1

公开(公告)日：2024-04-30

申请号：US17381833

申请日：2021-07-21

Applicant: Amazon Technologies, Inc.

Inventor： Ria Chakraborty ,  Madhur Popli ,  Rachit Lamba ,  Santosh Kumar Sahu ,  Rishi Kishore Verma

IPC: G06V10/00 ,  G06F18/21 ,  G06F18/214 ,  G06F18/22 ,  G06F18/2413 ,  G06F18/40 ,  G06N3/04 ,  G06N3/08 ,  G06T7/73 ,  G06V10/75 ,  G06F3/0482

CPC classification number: G06F18/2148 ,  G06F18/2155 ,  G06F18/2163 ,  G06F18/2178 ,  G06F18/22 ,  G06F18/2413 ,  G06F18/40 ,  G06N3/04 ,  G06N3/08 ,  G06T7/73 ,  G06V10/751 ,  G06F3/0482 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06V2201/09

Abstract: Techniques are generally described for machine learning exampled-based annotation of image data. In some examples, a first machine learning model may receive a query image comprising a first depiction of an object-of-interest. In some examples, the first machine learning model may receive a target image representing a scene in which a second depiction of the object-of-interest is visually represented. In various examples, the first machine learning model may generate annotated output image data that identifies a location of the second depiction of the object-of-interest within the target image. In some examples, an object detection model may be trained based at least in part on the annotated output image data.