公开(公告)号：US11734783B2

公开(公告)日：2023-08-22

申请号：US16713743

申请日：2019-12-13

Applicant: Tata Consultancy Services Limited

Inventor： Prasant Kumar Misra ,  Arunchandar Vasan ,  Krishna Kumar Sunil Komdam ,  Anand Sivasubramaniam ,  Alok Ranjan

IPC: G06K9/00 ,  G06K9/62 ,  G06Q50/30 ,  G06V20/58 ,  G06V20/10 ,  G06F18/23 ,  G06F18/214

CPC classification number: G06Q50/30 ,  G06F18/214 ,  G06F18/23 ,  G06V20/10 ,  G06V20/582 ,  G06V20/584 ,  G06V2201/07 ,  G06V2201/08 ,  G06V2201/10

Abstract: This disclosure relates generally to method and system for detecting on-street parking violations. The method include capturing, by using an media capturing device embodied in an electronic device mounted in a vehicle, a video stream of a scene during a trip of the vehicle. The video stream is processed at the electronic device to identify target objects such as no-parking signage and vehicles parked in the vicinity thereof. A meta-information associated with the target objects is stored in form of a short-term historian in a repository associated with the electronic device. The absolute locations of the target objects are determined and the historian is updated with the values of the absolute locations. A set of unique target objects is determined from amongst the target objects and a meta-information associated with the unique objects is sent to a cloud server for determining parking violations.

公开(公告)号：US20230260396A1

公开(公告)日：2023-08-17

申请号：US17805296

申请日：2022-06-03

Applicant: Hayden Al Technologies, Inc.

Inventor： Bo SHEN ,  Bryan John SHEA ,  Stuart Montagu MCKEE

IPC: G08G1/017 ,  G06F21/62 ,  H04L9/32 ,  H04L9/00 ,  G06V10/82 ,  G06V20/62

CPC classification number: G08G1/0175 ,  G06F21/6254 ,  H04L9/3236 ,  H04L9/50 ,  G06V10/82 ,  G06V20/625 ,  G06V2201/07 ,  G06V2201/08

Abstract: Disclosed herein are methods and systems for managing traffic violation or enforcement data using a distributed ledger. The distributed ledger provides a transparent chain of custody/evidence related to all digital interactions with traffic violation or enforcement data. The distributed ledger can be audited for data accuracy and integrity by nodes making up the system each time one of the nodes interacts with the traffic violation or enforcement data. For example, a digital evidence package related to a traffic violation event can be generated by a node within the system and a package digest can be logged in the distributed ledger beginning with the creation of the digital evidence package and each time that the digital evidence package is processed, modified, or reviewed by nodes within the system.

公开(公告)号：US20230252806A1

公开(公告)日：2023-08-10

申请号：US18147995

申请日：2022-12-29

Applicant: Agot Co.

Inventor： Evan DeSantola ,  Alex Litzenberger ,  Rassoul Mesbah ,  Prashasti Sar

IPC: G06V20/68 ,  G06Q50/12 ,  G06V10/764 ,  G06V20/00 ,  G06T7/70 ,  G06V20/52 ,  G06Q10/0631 ,  G06V10/70 ,  G06T7/20 ,  H04N7/18 ,  G06N20/00 ,  G06V20/20 ,  G06V20/64 ,  G06F3/0482 ,  G06T7/11 ,  G01B11/22 ,  G01S17/89 ,  G06Q20/20 ,  G06F18/214 ,  H04N23/90

CPC classification number: G06V20/68 ,  G06Q50/12 ,  G06V10/765 ,  G06V20/36 ,  G06T7/70 ,  G06V20/52 ,  G06Q10/063112 ,  G06V10/70 ,  G06T7/20 ,  H04N7/18 ,  G06N20/00 ,  G06V20/20 ,  G06V20/64 ,  G06F3/0482 ,  G06T7/11 ,  G01B11/22 ,  G01S17/89 ,  G06Q20/20 ,  G06F18/214 ,  H04N23/90 ,  G06T2200/24 ,  G06V2201/08 ,  G06T2207/20081 ,  G06T2207/30232 ,  G06T2207/10028

Abstract: The subject matter of this specification can be implemented in, among other things, methods, systems, computer-readable storage medium. A method can include receiving, by a processing device, image data including one or more image frames indicative of a current state of a meal preparation area. The processing device determines one of a meal preparation item or a meal preparation action associated with the current state of the kitchen based on the image data. The processing device receives order data comprising one or more pending meal orders. The processing device can determine an order preparation error based on the order data and at least one of the meal preparation item or the meal preparation action. The processing device causes the order preparation error to be displayed on a graphical user interface (GUI).

公开(公告)号：US11710158B2

公开(公告)日：2023-07-25

申请号：US16750815

申请日：2020-01-23

Applicant: Ford Global Technologies, LLC

Inventor： Pankaj Kumar ,  Avisek Naug ,  Imad Makki ,  Steven Joseph Szwabowski

IPC: G06Q30/0283 ,  G06N3/088 ,  G06V10/44 ,  G06F18/214 ,  G06F18/2132 ,  G06F18/21 ,  G06N3/045 ,  G06V10/764 ,  G06V10/774 ,  G06V10/778 ,  G06V10/82 ,  G06V10/20 ,  G06V20/20

CPC classification number: G06Q30/0283 ,  G06F18/214 ,  G06F18/2132 ,  G06F18/2193 ,  G06N3/045 ,  G06N3/088 ,  G06V10/255 ,  G06V10/44 ,  G06V10/764 ,  G06V10/774 ,  G06V10/7796 ,  G06V10/82 ,  G06V20/20 ,  G06V2201/08

Abstract: A computer, including a processor and a memory, the memory including instructions to be executed by the processor to train a generative adversarial network (GAN) to reconstruct a missing portion of an image by determining a reconstructed portion of the image based on data from portions of the image surrounding the missing portion and compare an acquired image with the reconstructed portion of the image to determine a damaged portion. The instructions further include instructions to determine estimated damage based on the damaged portion.

公开(公告)号：US20230230421A1

公开(公告)日：2023-07-20

申请号：US17578677

申请日：2022-01-19

Applicant: TOYOTA MOTOR ENGINEERING & MANUFACTURING NORTH AMERICA, INC.

Inventor： SEYHAN UCAR ,  TAKAMASA HIGUCHI ,  KENTARO OGUCHI

IPC: G07C5/00 ,  G07C5/02 ,  G08G1/01 ,  G08G1/017 ,  G08G1/04 ,  G06V20/58

CPC classification number: G07C5/008 ,  G06V20/58 ,  G07C5/02 ,  G08G1/04 ,  G08G1/0112 ,  G08G1/0175 ,  G06V2201/08

Abstract: Systems and methods of unsafe driving detection are provided which share partial unsafe driving behavior analyses with others in order to ensure that unsafe driving behavior is detected as early as possible. For example, in response to an event which interrupts a first detecting vehicle from collecting additional driving behavior data associated with a subject vehicle, the first detecting vehicle may transfer driving behavior data it has already collected and processed, to another detecting entity (e.g., a second detecting vehicle) in observable range of the subject vehicle.

公开(公告)号：US20230215196A1

公开(公告)日：2023-07-06

申请号：US17912648

申请日：2021-03-11

Applicant: Sony Semiconductor Solutions Corporation

Inventor： Tatsuya Sakashita

IPC: G06V20/70 ,  G06T7/50 ,  G06V10/774 ,  G06V10/94

CPC classification number: G06V20/70 ,  G06T7/50 ,  G06V10/774 ,  G06V10/945 ,  G06T2200/24 ,  G06V2201/08 ,  G06T2207/20081 ,  G06T2207/30252 ,  G06T2207/20084

Abstract: An information processing apparatus according to an embodiment of the present technology includes a generation unit. The generation unit generates, with respect to a target object in an image for learning on the basis of input information regarding an outer shape of the target object, which is input from a user, a three-dimensional region surrounding the target object as a label. Accordingly, the annotation accuracy can be improved.

公开(公告)号：US20230206643A1

公开(公告)日：2023-06-29

申请号：US18088343

申请日：2022-12-23

Applicant: HANWHA TECHWIN CO., LTD.

Inventor： Chanyoung SOHN ,  Ga Young Kim

IPC: G06V20/52 ,  G06V40/10 ,  G06T7/73 ,  G06V10/764 ,  G06T7/60 ,  G06V10/26

CPC classification number: G06V20/52 ,  G06V40/10 ,  G06T7/74 ,  G06V10/764 ,  G06T7/60 ,  G06V10/26 ,  G06V2201/08 ,  G06T2207/30196 ,  G06T2207/30232

Abstract: Disclosed is a image processing apparatus and a method for controlling the image processing apparatus. The image processing apparatus according to an embodiment of the present disclosure may identify an object from an acquired image, determine whether the object is hidden by another object by using an aspect ratio of a bounding box of the detected object, and based on the object being hidden, estimate an entire length of the object based on coordinate information of the bounding box. Accordingly, the size information of the hidden object may be efficiently identified while a large amount of database is applied or resources of the apparatus is minimized. The present disclosure may be in connection with a surveillance camera, an automotive driving vehicle, an artificial intelligence module of at least one of a user terminal or a server, a robot, an augmented reality (AR) device, a virtual reality (VR) device, a device related to a 5G service, and the like.

公开(公告)号：US11686848B2

公开(公告)日：2023-06-27

申请号：US17007651

申请日：2020-08-31

Applicant: UATC, LLC

Inventor： Xuanyuan Tu ,  Sivabalan Manivasagam ,  Mengye Ren ,  Ming Liang ,  Bin Yang ,  Raquel Urtasun

IPC: G01S17/931 ,  G06N20/00 ,  G01S17/89 ,  G01S17/42 ,  G01S17/894 ,  G06V20/56 ,  G06V20/64 ,  G06F18/214 ,  G06F18/21 ,  G06V10/764 ,  G06V10/82

CPC classification number: G01S17/89 ,  G01S17/42 ,  G01S17/894 ,  G01S17/931 ,  G06F18/214 ,  G06F18/217 ,  G06N20/00 ,  G06V10/764 ,  G06V10/82 ,  G06V20/56 ,  G06V20/64 ,  G06V2201/07 ,  G06V2201/08

Abstract: Systems and methods for training object detection models using adversarial examples are provided. A method includes obtaining a training scene and identifying a target object within the training scene. The method includes obtaining an adversarial object and generating a modified training scene based on the adversarial object, the target object, and the training scene. The modified training scene includes the training scene modified to include the adversarial object placed on the target object. The modified training scene is input to a machine-learned model configured to detect the training object. A detection score is determined based on whether the training object is detected, and the machine-learned model and the parameters of the adversarial object are trained based on the detection output. The machine-learned model is trained to maximize the detection output. The parameters of the adversarial object are trained to minimize the detection output.

公开(公告)号：US20230199137A1

公开(公告)日：2023-06-22

申请号：US18112892

申请日：2023-02-22

Applicant: Panasonic Intellectual Property Management Co., Ltd.

Inventor： Yudai ISHIBASHI ,  Yoshimasa OKABE

IPC: H04N5/265 ,  H04N23/90 ,  G06T11/00 ,  G06V20/58 ,  H04N5/262 ,  B60R1/26

CPC classification number: H04N5/265 ,  H04N23/90 ,  G06T11/00 ,  G06V20/58 ,  H04N5/2628 ,  B60R1/26 ,  G06T2207/20221 ,  G06T2207/30252 ,  G06V2201/08 ,  B60R2300/105 ,  B60R2300/20 ,  B60R2300/303

Abstract: A display control apparatus includes a vehicle detector and a processor, the processor generating a background image of a vehicle, setting, when a surrounding vehicle is detected in a predetermined region, a second projection plane to a position at which the surrounding vehicle is detected, generating a surrounding vehicle image by projecting a plurality of captured images onto the second projection plane, and superimposing the surrounding vehicle image on the background image.

公开(公告)号：US11663799B1

公开(公告)日：2023-05-30

申请号：US17751371

申请日：2022-05-23

Applicant: CCC INTELLIGENT SOLUTIONS INC.

Inventor： Saeid Bagheri ,  Masatoshi Kato ,  Christoph Plenio

IPC: G06V10/10 ,  G06T7/00 ,  G06N20/00 ,  G06Q40/08 ,  G06V20/10 ,  G06F18/214 ,  H04N23/80

CPC classification number: G06V10/10 ,  G06F18/214 ,  G06N20/00 ,  G06Q40/08 ,  G06T7/0002 ,  G06V20/10 ,  H04N23/80 ,  G06T2207/30248 ,  G06V2201/08

Abstract: Techniques for automatic image tagging and selection at a mobile device include generating a smart image tagging model by first training an initial model based on different angles of image capture of subject vehicles, and then re-training the trained model using weights discovered from the first training and images that have been labeled with additional tags indicative of different vehicle portions and/or vehicle parameters. Nodes that are training-specific are removed from the re-trained model, and the lightweight model is serialized to generate the smart image tagging model. The generated model may autonomously execute at an imaging device to predict respective tags associated with a stream of frames; select, capture and store respective suitable frames as representative images corresponding to the predicted tags; and provide the set of representative images and associated tags for use in determining vehicle damage, insurance claims, and the like.