公开(公告)号：US11861885B2

公开(公告)日：2024-01-02

申请号：US16324915

申请日：2017-09-04

Applicant: Assaf Gavish ,  Asaf Levy ,  Yoav Gavish

Inventor： Assaf Gavish ,  Asaf Levy ,  Yoav Gavish

IPC: G06V10/82 ,  A01H6/28 ,  A01B79/00 ,  G06V20/10 ,  G06F18/2413 ,  G06V10/764 ,  G06V20/60

CPC classification number: G06V10/82 ,  A01B79/005 ,  A01H6/28 ,  G06F18/24143 ,  G06V10/764 ,  G06V20/188 ,  G06V20/60

Abstract: A method and system for characterization of Cannabaceae plants using macro photography images is disclosed. The method comprises the steps of receiving one or more macro photography images of a Cannabaceae plant; performing feature extraction analysis of trichomes using image processing, and performing plant characterization analysis using a neural network which analyzes the macro photography images. The training phase of the neural network comprises using results of chemical composition laboratory tests performed on the plants for which the macro photography images have been used in the training phase. The invention calculates and reports an assessment of maturity of the plant for harvesting, diagnosis of the existence of diseases, insects, or pests, assessment of the presence and concentrations of central ingredients, recommendations for treatment during plants drying, curing or storage production processes, and assessment of the quality and pricing of Cannabaceae plants products.

公开(公告)号：US11861850B2

公开(公告)日：2024-01-02

申请号：US18171066

申请日：2023-02-17

Applicant: STATS LLC

Inventor： Long Sha ,  Sujoy Ganguly ,  Xinyu Wei ,  Patrick Joseph Lucey ,  Aditya Cherukumudi

IPC: G06T7/20 ,  G06N3/08 ,  G06T7/73 ,  G06T7/80 ,  G06T7/00 ,  G06T7/70 ,  H04N21/44 ,  G06V20/40 ,  G06V40/20 ,  G06F18/22 ,  G06F18/214 ,  G06F18/232 ,  G06F18/2135 ,  G06F18/2413 ,  G06V10/764 ,  G06V10/82 ,  G06V10/44

CPC classification number: G06T7/20 ,  G06F18/214 ,  G06F18/2135 ,  G06F18/22 ,  G06F18/232 ,  G06F18/2413 ,  G06N3/08 ,  G06T7/70 ,  G06T7/73 ,  G06T7/80 ,  G06T7/97 ,  G06V10/454 ,  G06V10/764 ,  G06V10/82 ,  G06V20/42 ,  G06V20/46 ,  G06V20/48 ,  G06V20/49 ,  G06V40/20 ,  H04N21/44008 ,  G06T2207/10016 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30221 ,  G06T2207/30244 ,  G06V20/44

Abstract: A system and method of re-identifying players in a broadcast video feed are provided herein. A computing system retrieves a broadcast video feed for a sporting event. The broadcast video feed includes a plurality of video frames. The computing system generates a plurality of tracks based on the plurality of video frames. Each track includes a plurality of image patches associated with at least one player. Each image patch of the plurality of image patches is a subset of the corresponding frame of the plurality of video frames. For each track, the computing system generates a gallery of image patches. A jersey number of each player is visible in each image patch of the gallery. The computing system matches, via a convolutional autoencoder, tracks across galleries. The computing system measures, via a neural network, a similarity score for each matched track and associates two tracks based on the measured similarity.

公开(公告)号：US11860978B2

公开(公告)日：2024-01-02

申请号：US18061474

申请日：2022-12-04

Applicant: CHENGDU QINCHUAN IOT TECHNOLOGY CO., LTD.

Inventor： Zehua Shao ,  Haitang Xiang ,  Yaqiang Quan ,  Bin Liu

IPC: G06F18/2413 ,  G06F18/23 ,  G06F11/30

CPC classification number: G06F18/2413 ,  G06F11/3089 ,  G06F18/23

Abstract: The present disclosure provides an early warning method and an early warning system for a detection device located at an energy metering point of natural gas, comprising: obtaining a first detection data set collected by the detection device located at the energy metering point of the natural gas, determining a first cluster center set through clustering a first historical detection data set, determining a first vector corresponding to the first detection data set based on the first detection data set, determining a first target cluster center based on the first vector and the first cluster center set; and determining whether the detection device is abnormal based on a distance between the first vector and the first target cluster center.

公开(公告)号：US11853882B2

公开(公告)日：2023-12-26

申请号：US17153014

申请日：2021-01-20

Applicant: TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED

Inventor： Wenbing Huang ,  Yu Rong ,  Junzhou Huang

IPC: G06F18/213 ,  G06N3/08 ,  G06F18/214 ,  G06F18/2413 ,  G06N7/01

CPC classification number: G06N3/08 ,  G06F18/213 ,  G06F18/214 ,  G06F18/24147 ,  G06N7/01

Abstract: The present disclosure describes methods, apparatus, and storage medium for node classification and training a node classification model. The method includes obtaining a target node subset and a neighbor node subset corresponding to the target node subset from a sample node set labeled with a target node class, a neighbor node in the neighbor node subset being associated with a target node in the target node subset; extracting a feature subset of the target node subset based on the neighbor node subset by using a node classification model, the feature subset comprising a feature vector of the target node; performing class prediction for the target node subset according to the feature subset, to obtain a predicted class probability subset; and training the node classification model with a target model parameter according to the predicted class probability subset and a target node class subset of the target node subset.

公开(公告)号：US20230410495A1

公开(公告)日：2023-12-21

申请号：US18241709

申请日：2023-09-01

Applicant: Align Technology, Inc.

Inventor： Ya Xue ,  Yingjie Li ,  Chao Shi ,  Aleksandr Anikin ,  Mikhail Toporkov ,  Aleksandr Sergeevich Karsakov

IPC: G06V10/82 ,  G06V10/44 ,  G06F18/2413 ,  G06V30/19 ,  G06T7/13 ,  G06T7/00

CPC classification number: G06V10/82 ,  G06V10/44 ,  G06F18/24143 ,  G06V30/19173 ,  G06T7/13 ,  G06T7/0012 ,  G06V2201/033 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/20132 ,  G06T2207/30004

Abstract: A method includes receiving an image of a face, processing the image using a first trained machine learning model to determine a bounding shape around teeth in the image, cropping the image based on the bounding shape to produce a cropped image, processing the cropped image using an edge detection operation to generate edge data for the cropped image, and processing the cropped image and the edge data using a second trained machine learning model to label edges in the cropped image.

公开(公告)号：US11836240B2

公开(公告)日：2023-12-05

申请号：US18157154

申请日：2023-01-20

Applicant: Intel Corporation

Inventor： Yen-Kuang Chen ,  Shao-Wen Yang ,  Ibrahima J. Ndiour ,  Yiting Liao ,  Vallabhajosyula S. Somayazulu ,  Omesh Tickoo ,  Srenivas Varadarajan

IPC: G06F21/44 ,  H04L9/06 ,  G06F21/64 ,  G06F21/53 ,  G06N5/022 ,  G06F21/45 ,  H04L9/32 ,  H04W4/70 ,  G06F16/538 ,  G06F16/535 ,  G06F16/54 ,  G06F21/62 ,  G06F9/50 ,  G06N3/04 ,  G06N3/063 ,  G06V10/44 ,  G06V20/00 ,  G06V40/20 ,  G06V40/16 ,  G06F9/48 ,  H04L67/51 ,  G06T7/11 ,  G06V10/96 ,  G06V30/262 ,  G06K15/02 ,  G06F18/24 ,  G06F18/21 ,  G06F18/22 ,  G06F18/211 ,  G06F18/213 ,  G06F18/2413 ,  G06N3/045 ,  G06V30/19 ,  G06V10/82 ,  G06V10/94 ,  G06V10/75 ,  G06V10/20 ,  G06V10/40 ,  G06N3/08 ,  H04L67/12 ,  H04N19/80 ,  G06F16/951 ,  H04N19/46 ,  G06T7/70 ,  H04W12/02 ,  H04L9/00 ,  H04N19/12 ,  H04N19/124 ,  H04N19/167 ,  H04N19/172 ,  H04N19/176 ,  H04N19/44 ,  H04N19/48 ,  H04N19/513 ,  G06T7/20 ,  G06F18/243 ,  G06V30/194 ,  H04N19/42 ,  H04N19/625 ,  H04N19/63 ,  G06T7/223 ,  H04L67/10

CPC classification number: G06F21/44 ,  G06F9/4881 ,  G06F9/5044 ,  G06F9/5066 ,  G06F9/5072 ,  G06F16/535 ,  G06F16/538 ,  G06F16/54 ,  G06F16/951 ,  G06F18/21 ,  G06F18/211 ,  G06F18/213 ,  G06F18/2163 ,  G06F18/22 ,  G06F18/24 ,  G06F18/24143 ,  G06F21/45 ,  G06F21/53 ,  G06F21/6254 ,  G06F21/64 ,  G06K15/1886 ,  G06N3/04 ,  G06N3/045 ,  G06N3/063 ,  G06N3/08 ,  G06N5/022 ,  G06T7/11 ,  G06T7/70 ,  G06V10/20 ,  G06V10/40 ,  G06V10/454 ,  G06V10/75 ,  G06V10/82 ,  G06V10/95 ,  G06V10/96 ,  G06V20/00 ,  G06V30/19173 ,  G06V30/274 ,  G06V40/161 ,  G06V40/20 ,  H04L9/0643 ,  H04L9/3239 ,  H04L67/12 ,  H04L67/51 ,  H04N19/46 ,  H04N19/80 ,  H04W4/70 ,  G06F18/24323 ,  G06F2209/503 ,  G06F2209/506 ,  G06F2221/2117 ,  G06T7/20 ,  G06T7/223 ,  G06T2207/10016 ,  G06T2207/20021 ,  G06T2207/20024 ,  G06T2207/20052 ,  G06T2207/20056 ,  G06T2207/20064 ,  G06T2207/20084 ,  G06T2207/20221 ,  G06T2207/30242 ,  G06V30/194 ,  G06V2201/10 ,  H04L9/50 ,  H04L67/10 ,  H04N19/12 ,  H04N19/124 ,  H04N19/167 ,  H04N19/172 ,  H04N19/176 ,  H04N19/42 ,  H04N19/44 ,  H04N19/48 ,  H04N19/513 ,  H04N19/625 ,  H04N19/63 ,  H04W12/02

Abstract: In one embodiment, an apparatus comprises a memory and a processor. The memory is to store visual data associated with a visual representation captured by one or more sensors. The processor is to: obtain the visual data associated with the visual representation captured by the one or more sensors, wherein the visual data comprises uncompressed visual data or compressed visual data; process the visual data using a convolutional neural network (CNN), wherein the CNN comprises a plurality of layers, wherein the plurality of layers comprises a plurality of filters, and wherein the plurality of filters comprises one or more pixel-domain filters to perform processing associated with uncompressed data and one or more compressed-domain filters to perform processing associated with compressed data; and classify the visual data based on an output of the CNN.

公开(公告)号：US20230386186A1

公开(公告)日：2023-11-30

申请号：US18202941

申请日：2023-05-28

Applicant: Edge 3 Technologies, Inc.

Inventor： Tarek El Dokor

IPC: G06V10/776 ,  G06V20/10 ,  G06V20/52 ,  G06V40/16 ,  G06V40/20 ,  G06F18/24 ,  G06F18/21 ,  G06F18/2413 ,  G06V10/764 ,  G06N3/02 ,  H04N5/33

CPC classification number: G06V10/776 ,  G06V20/10 ,  G06V20/52 ,  G06V40/16 ,  G06V40/20 ,  G06F18/24 ,  G06F18/217 ,  G06F18/24133 ,  G06V10/764 ,  G06N3/02 ,  H04N5/33

Abstract: A method and apparatus for processing image data is provided. The method includes the steps of employing a main processing network for classifying one or more features of the image data, employing a monitor processing network for determining one or more confusing classifications of the image data, and spawning a specialist processing network to process image data associated with the one or more confusing classifications.

公开(公告)号：US11822623B2

公开(公告)日：2023-11-21

申请号：US17178310

申请日：2021-02-18

Applicant: CASIO COMPUTER CO., LTD.

Inventor： Junichiro Soejima

IPC: G06F18/23213 ,  G01P15/08 ,  G06F18/2413

CPC classification number: G06F18/23213 ,  G01P15/08 ,  G06F18/24137

Abstract: One aspect of the present disclosure relates to a traveling amount estimation apparatus, comprising: at least one processor; and at least one memory that stores a program executed by the processor, wherein the processor is configured to: extract a feature amount from sensor data obtained from a traveling user and relating to traveling of the user; determine to which cluster the feature amount belongs; and estimate a traveling amount of the user from the feature amount in accordance with a regression function for the determined cluster.

公开(公告)号：US11818022B2

公开(公告)日：2023-11-14

申请号：US16917391

申请日：2020-06-30

Applicant: Pensando Systems Inc.

Inventor： Lakshmi Narasimhan Seshan ,  Bharat Kumar Bandaru

IPC: H04L43/026 ,  H04L45/00 ,  H04L45/42 ,  H04L43/16 ,  H04L45/30 ,  G06F18/214 ,  G06F18/2413

CPC classification number: H04L43/026 ,  G06F18/214 ,  G06F18/2413 ,  H04L43/16 ,  H04L45/30 ,  H04L45/38 ,  H04L45/42

Abstract: Methods and system for directing traffic flows to a fast data path or a slow data path are disclosed. Parsers can produce packet header vectors (PHVs) for use in match-action units. The PHVs are also used to generate feature vectors for the traffic flows. A flow training engine produces a classification model. Feature vectors input to the classification model result in output predictions predicting if a traffic flow will be long lived or short lived. The classification models are used by network appliances to install traffic flows into fast data paths or the slow data paths based on the predictions.

公开(公告)号：US11810669B2

公开(公告)日：2023-11-07

申请号：US16548256

申请日：2019-08-22

Applicant: Kenneth Neumann

Inventor： Kenneth Neumann

IPC: G16H50/20 ,  G06F40/20 ,  G06F18/214 ,  G06F18/2413 ,  G06V10/764 ,  G06V10/774

CPC classification number: G16H50/20 ,  G06F18/2148 ,  G06F18/2413 ,  G06F40/20 ,  G06V10/764 ,  G06V10/7747

Abstract: A system for generating a descriptor trail using artificial intelligence. The system includes at least a server configured to receive at least a biological extraction. At least a server is configured to generate a prognostic output as a function of at least a biological extraction. At least a server is configured to generate an ameliorative output as a function of a prognostic output. The system includes a descriptor generator module operating on at least a server. A descriptor generator module is configured to generate at least a descriptor trail from a descriptor trail data structure wherein the descriptor trail further comprises at least an element of diagnostic data.