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公开(公告)号：US20230389817A1
公开(公告)日：2023-12-07
申请号：US18246487
申请日：2020-10-29
Inventor： Tianqi Guo , Qian Lin , Jan Allebach
CPC classification number: A61B5/0816 , A61B5/113 , A61B5/1128 , G06V40/20 , G06V40/10 , G06V10/82 , G06V10/273
Abstract: In some examples, a non-transitory computer-readable medium stores executable code, which, when executed by a processor, causes the processor to receive a video of at least part of a human torso, use a neural network to produce multiple vector fields based on the video, the multiple vector fields representing movement of the human torso, and determine a respiration rate of the human torso using the multiple vector fields.
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公开(公告)号：US11507389B2
公开(公告)日：2022-11-22
申请号：US16078369
申请日：2016-09-29
Applicant: HEWLETT-PACKARD DEVELOPMENT COMPANY, L.P.
Inventor： Alexander Wayne Clark , Kent E. Biggs , Qian Lin , Madhu Sudan Athreya
IPC: G06F9/4401 , G06F3/16 , G09G3/22 , G06V20/10 , G06V40/16
Abstract: Examples disclosed herein provide the ability for a computing device to adjust settings on a computing device. In one example method, the computing device captures, via a first sensor of a computing device, images of an environment that the computing device is currently in, and detects objects in the environment as captured by the images. As an example, the computing device determines a location of the environment based on contextual data gathered from the detected objects and adjusts a setting on the computing device based on the determined location.
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公开(公告)号：US11443551B2
公开(公告)日：2022-09-13
申请号：US16612782
申请日：2017-10-24
Applicant: Hewlett-Packard Development Company, L.P.
Inventor： Harold Merkel , Qian Lin , Guoxing Yang
IPC: G06V40/16 , G06T7/55 , G06F16/535 , G06V10/44 , G06V40/10
Abstract: In example implementations, a method is provided. The method may be executed by a processor. The method includes receiving an image. The image is analyzed to obtain facial features. Contextual information is obtained and a vector including a facial feature class of the facial features and contextual feature classes of the contextual information is generated. A facial recognition is then performed based on the vector.
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公开(公告)号：US11176679B2
公开(公告)日：2021-11-16
申请号：US16618599
申请日：2017-10-24
Applicant: Hewlett-Packard Development Company, L.P.
Inventor： Qian Lin
Abstract: In example implementations, a method is provided. The method may be executed by a processor. The method includes receiving an image. A person from a plurality of people within the image is identified. The person is segmented from the image. A background image of the image is replaced with a clean background image to remove the plurality of people from the image except the person that is identified.
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公开(公告)号：US20210337073A1
公开(公告)日：2021-10-28
申请号：US17284110
申请日：2018-12-20
Applicant: Hewlett-Packard Development Company, L.P.
Inventor： Qian Lin , Otavio Basso Gomes , Augusto Cavalcante Valente , Guilherme Augusto Silva Megeto , Marcos Henrique Cascone , Thomas da Silva Paula , Fabio Vinicius Moreira Perez
Abstract: An example of an apparatus is provided. The apparatus includes an extraction engine to extract a plurality of patches from an image of a printed document. The apparatus further includes a classification engine to analyze each patch of the plurality of patches and to assign a defect probability to each patch of the plurality of patches. The apparatus also includes a rendering engine to generate a map based on the defect probability of each patch of the plurality of patches. The map is to identify defects in the printed document.
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Patent Agency Ranking
公开(公告)号：US20240404268A1
公开(公告)日：2024-12-05
申请号：US18699701
申请日：2021-10-14
Applicant: Hewlett-Packard Development Company, L.P.
Inventor： Qian Lin , Augusto Valente , Otavio Gomes
IPC: G06V10/82 , G06V10/774 , G06V10/776
Abstract: In some examples, a computing device can include a processing resource and a memory resource storing instructions to cause the processing resource to cause a convolutional neural network (CNN) model to be trained with an initial training data set to detect an object included in annotated images included in the initial training data set, cause the trained CNN model to perform inferencing on unannotated images included in an inference data set to detect the object in the unannotated images, determine an error rate of the trained CNN model, and cause the trained CNN model to be further trained based on the error rate.
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公开(公告)号：US20240404017A1
公开(公告)日：2024-12-05
申请号：US18698757
申请日：2021-10-13
Inventor： Xiaoyu Xiang , Qian Lin , Jan Allebach , Tianqi Guo
IPC: G06T5/60 , G06T3/4046 , G06T7/10
Abstract: In some examples, a computing device can include a processor resource and a non-transitory memory resource storing machine-readable instructions stored thereon that, when executed, cause the processor resource to identify a base resolution of a captured image having a base image quality, perform, via an individual neural network, neural network calculations on the captured image to form an enhanced image having an resolution that is higher than the base resolution and image quality that is higher than the base image quality.
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公开(公告)号：US11954905B2
公开(公告)日：2024-04-09
申请号：US17434527
申请日：2019-06-28
Inventor： Yang Cheng , Xiaoyu Xiang , Shaoyuan Xu , Qian Lin , Jan Philip Allebach
IPC: G06V10/82 , G06T7/73 , G06V10/764 , G06V40/16
CPC classification number: G06V10/82 , G06T7/74 , G06V10/764 , G06V40/165 , G06V40/171 , G06V40/174 , G06V40/176 , G06T2207/20224 , G06T2207/30201
Abstract: An example system includes: a landmark detection engine to detect landmark positions of landmarks in images based on facial detection; an optical flow landmark engine to determine the landmark positions in the images based on optical flow of the landmarks between the images; a landmark difference engine to determine, for a landmark in a given image: a distance between a detected landmark position and an optical flow landmark position of the landmark; and a weighted landmark determination engine to determine, for a first and second image, a position for the landmark in the second image based on: a respective detected landmark position and a respective optical flow position of the landmark in the second image; and respective distances, determined with the landmark difference engine, between a first detected landmark position of the landmark in the first image and respective optical flow landmark positions for the first and second images.
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公开(公告)号：US20240071031A1
公开(公告)日：2024-02-29
申请号：US17821575
申请日：2022-08-23
Inventor： Yang Cheng , Qian Lin , Jan Philip Allebach
CPC classification number: G06V10/255 , G06T15/205 , G06V10/753 , G06V10/94 , G06T2200/24
Abstract: An example device is described for facilitating polygon localization. In various aspects, the device can comprise a processor. In various instances, the device can comprise a non-transitory machine-readable memory that can store machine-readable instructions. In various cases, the processor can execute the machine-readable instructions, which can cause the processor to localize a polygon depicted in an image, based on execution of a deep learning pipeline. In various aspects, the deep learning pipeline can comprise a circular-softmax block.
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公开(公告)号：US20220351427A1
公开(公告)日：2022-11-03
申请号：US17762102
申请日：2019-10-16
Applicant: Hewlett-Packard Development Company, L.P.
Inventor： Qian Lin , Augusto Cavalcante Valente , Deangeli Gomes Neves , Guilherme Augusto Silva Megeto
Abstract: Examples of methods for training using rendered images are described herein. In some examples, a method may include, for a set of iterations, randomly positioning a three-dimensional (3D) object model in a virtual space with random textures. In some examples, the method may include, for the set of iterations, rendering a two-dimensional (2D) image of the 3D object model in the virtual space and a corresponding annotation image. In some examples, the method may include training a machine learning model using the rendered 2D images and corresponding annotation images.
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