公开(公告)号：US20240153044A1

公开(公告)日：2024-05-09

申请号：US18405440

申请日：2024-01-05

申请人： Perceive Corporation

发明人： Andrew C. Mihal ,  Steven L. Teig ,  Eric A. Sather

IPC分类号： G06T5/70 ,  G06N3/04 ,  G06N3/044 ,  G06N3/049 ,  G06N3/063 ,  G06N3/084 ,  G06N5/046 ,  G06N20/10

CPC分类号： G06T5/70 ,  G06N3/04 ,  G06N3/044 ,  G06N3/049 ,  G06N3/063 ,  G06N3/084 ,  G06N5/046 ,  G06N20/10 ,  G06T2207/10016 ,  G06T2207/20081 ,  G06T2207/20084

摘要： Some embodiments provide a neural network inference circuit for executing a neural network that includes multiple nodes that use state data from previous executions of the neural network. The neural network inference circuit includes (i) a set of computation circuits configured to execute the nodes of the neural network and (ii) a set of memories configured to implement a set of one or more registers to store, while executing the neural network for a particular input, state data generated during at least two executions of the network for previous inputs. The state data is for use by the set of computation circuits when executing a set of the nodes of the neural network for the particular input.

公开(公告)号：US11979350B1

公开(公告)日：2024-05-07

申请号：US17688793

申请日：2022-03-07

申请人： Verana Networks, Inc.

发明人： Vedat Eyuboglu ,  Evan Sabri Eyuboglu ,  Kenneth D. Jones

IPC分类号： H04L5/00 ,  G06N3/044 ,  H04B7/0413 ,  H04B7/06 ,  H04L1/1812 ,  H04L25/02 ,  H04L41/16 ,  H04W80/02 ,  H04W84/18

CPC分类号： H04L5/005 ,  G06N3/044 ,  H04B7/0413 ,  H04B7/0626 ,  H04L1/1819 ,  H04L25/0226 ,  H04L41/16 ,  H04W80/02 ,  H04L5/0007 ,  H04W84/18

摘要： Among other things, aspects, features, and implementations of wireless mesh networks and wireless mesh network devices are described.

公开(公告)号：US11978245B2

公开(公告)日：2024-05-07

申请号：US16050329

申请日：2018-07-31

申请人： Baidu Online Network Technology (Beijing) Co., Ltd.

发明人： Tao He ,  Gang Zhang ,  Jingtuo Liu

IPC分类号： G06V10/82 ,  G06F18/214 ,  G06F18/2413 ,  G06N3/044 ,  G06N3/045 ,  G06N3/047 ,  G06N3/08 ,  G06N3/084 ,  G06N7/00 ,  G06N7/01 ,  G06N20/00 ,  G06N20/10 ,  G06T7/00 ,  G06T7/246 ,  G06T11/00 ,  G06V10/764 ,  G06V40/16

CPC分类号： G06V10/82 ,  G06F18/214 ,  G06F18/2413 ,  G06N3/044 ,  G06N3/045 ,  G06N3/047 ,  G06N3/08 ,  G06N3/084 ,  G06N7/00 ,  G06N20/00 ,  G06T7/251 ,  G06T7/97 ,  G06T11/00 ,  G06V10/764 ,  G06V40/165 ,  G06V40/167 ,  G06V40/168 ,  G06V40/172 ,  G06N7/01 ,  G06N20/10 ,  G06T2207/20081 ,  G06T2207/30201

摘要： The present disclosure discloses a method and apparatus for generating an image. A specific embodiment of the method comprises: acquiring at least two frames of facial images extracted from a target video; and inputting the at least two frames of facial images into a pre-trained generative model to generate a single facial image. The generative model updates a model parameter using a loss function in a training process, and the loss function is determined based on a probability of the single facial generative image being a real facial image and a similarity between the single facial generative image and a standard facial image. According to this embodiment, authenticity of the single facial image generated by the generative model may be enhanced, and then a quality of a facial image obtained based on the video is improved.

公开(公告)号：US11977995B2

公开(公告)日：2024-05-07

申请号：US17591022

申请日：2022-02-02

申请人： CAPITAL ONE SERVICES, LLC

发明人： Ashish Bansal ,  Jonathan Stahlman

IPC分类号： G06Q10/063 ,  G06F15/76 ,  G06N3/02 ,  G06N3/044 ,  G06N3/045 ,  G06N5/01 ,  G06N5/025 ,  G06N5/046 ,  G06N7/01 ,  G06N20/00 ,  G06N20/10 ,  G06N20/20 ,  G06Q10/0633 ,  G06Q40/12

CPC分类号： G06Q10/063 ,  G06F15/76 ,  G06N3/02 ,  G06N5/01 ,  G06N5/025 ,  G06N5/046 ,  G06N7/01 ,  G06N20/00 ,  G06N20/20 ,  G06Q10/0633 ,  G06N3/044 ,  G06N3/045 ,  G06N20/10 ,  G06Q40/12

摘要： An artificial intelligence system for communicating predicted hours of operation to a client device. The system may include a processor in communication with a client device and a database; and a storage medium storing instructions. When executed, the instructions in the storage medium configure the processor to: receive, from the client device, a request for hours of operation of a merchant, the request specifying a day of the week; obtain, from the database in response to the request, a set of credit card authorizations associated with the merchant; determine a selected day authorizations subset by selecting, from the set of credit card authorizations, credit card authorizations issued on the specified day of the week; generate a posted transaction array based on the selected day authorizations subset, the posted transaction array may include a plurality of time intervals and numbers of transactions for the time intervals; generate a predictions list based on the posted transaction array, the predictions list including the time intervals and prediction indications for the time intervals; and communicate the predictions list to the client device.

公开(公告)号：US11977561B2

公开(公告)日：2024-05-07

申请号：US16779473

申请日：2020-01-31

申请人： Walmart Apollo, LLC

发明人： Yanxin Pan ,  Swagata Chakraborty ,  Abhinandan Krishnan ,  Abon Chaudhuri ,  Aakash Mayur Mehta ,  Edison Mingtao Zhang ,  Kyu Bin Kim

IPC分类号： G06F16/28 ,  G06F16/2455 ,  G06N3/044 ,  G06N3/045 ,  G06N3/08 ,  G06Q30/0601

CPC分类号： G06F16/285 ,  G06F16/24553 ,  G06N3/044 ,  G06N3/045 ,  G06N3/08 ,  G06Q30/0603 ,  G06Q30/0641

摘要： A method including obtaining image data and attribute information of a first item in an item catalog. The method also can include generating candidate variant items from the item catalog for the first item using a combination of (a) a k-nearest neighbors approach to search for first candidate variant items based on text embeddings for the attribute information of the first item, and (b) an elastic search approach to search for second candidate variant items based on image embeddings for the image data of the first item. The method additionally can include performing respective classifications based on respective pairs comprising the first item and each of the candidate variant items to filter the candidate variant items. The method further can include determining a respective distance between the first item and each of the candidate variant items, as filtered. The method additionally can include determining one or more items in the candidate variant items, as filtered, to include in a variant group for the first item, based on a decision function using a predetermined threshold and the respective distance for the each of the candidate variant items, as filtered. Other embodiments are described.

公开(公告)号：US20240142321A1

公开(公告)日：2024-05-02

申请号：US18378230

申请日：2023-10-10

申请人： Board of Trustees of Michigan State University

发明人： Xiaobo TAN ,  Hongyang SHI ,  Nelson SEPULVEDA ,  Claudia CHEN ,  Yu MEI

IPC分类号： G01L1/18 ,  G01L5/00 ,  G06N3/044 ,  G06N3/08

CPC分类号： G01L1/18 ,  G01L5/0061 ,  G06N3/044 ,  G06N3/08

摘要： A soft pressure sensing apparatus is provided. In one aspect of the present pressure sensing apparatus, a polymeric member, including conductive particles therein, is located between offset angled and crossing sets of electrodes. A further aspect includes a controller configured to calculate at least one regularized least-squares algorithm, to reduce cross-talk between the resistive members. In another aspect, a pressure sensor apparatus includes a piezoresistive film encapsulated between layers of substantially perpendicular electrodes to create a resistor network circuit where the ability to reconstruct cell resistance from measured two-point resistance. A method of manufacturing a pressure sensor includes using a mechanical vinyl cutter for the electrodes and/or piezoelectric resistive members.

公开(公告)号：US11972339B2

公开(公告)日：2024-04-30

申请号：US17040299

申请日：2019-03-22

申请人： Google LLC

发明人： Pararth Shah ,  Dilek Hakkani-Tur ,  Juliana Kew ,  Marek Fiser ,  Aleksandra Faust

IPC分类号： G06N3/008 ,  B25J9/16 ,  B25J13/08 ,  G05B13/02 ,  G05D1/00 ,  G05D1/02 ,  G06F18/21 ,  G06N3/044 ,  G06T7/593 ,  G06V20/10 ,  G06V30/262 ,  G10L15/16 ,  G10L15/18 ,  G10L15/22 ,  G10L25/78

CPC分类号： G06N3/008 ,  B25J9/161 ,  B25J9/162 ,  B25J9/163 ,  B25J9/1697 ,  B25J13/08 ,  G05B13/027 ,  G05D1/0221 ,  G06F18/21 ,  G06N3/044 ,  G06T7/593 ,  G06V20/10 ,  G06V30/274 ,  G10L15/16 ,  G10L15/1815 ,  G10L15/22 ,  G10L25/78 ,  G10L2015/223

摘要： Implementations relate to using deep reinforcement learning to train a model that can be utilized, at each of a plurality of time steps, to determine a corresponding robotic action for completing a robotic task. Implementations additionally or alternatively relate to utilization of such a model in controlling a robot. The robotic action determined at a given time step utilizing such a model can be based on: current sensor data associated with the robot for the given time step, and free-form natural language input provided by a user. The free-form natural language input can direct the robot to accomplish a particular task, optionally with reference to one or more intermediary steps for accomplishing the particular task. For example, the free-form natural language input can direct the robot to navigate to a particular landmark, with reference to one or more intermediary landmarks to be encountered in navigating to the particular landmark.

公开(公告)号：US11967150B2

公开(公告)日：2024-04-23

申请号：US18108873

申请日：2023-02-13

申请人： DeepMind Technologies Limited

发明人： Simon Osindero ,  Joao Carreira ,  Viorica Patraucean ,  Andrew Zisserman

IPC分类号： G06V20/40 ,  G06N3/044 ,  G06N3/045 ,  G06N3/049 ,  G06T1/20

CPC分类号： G06V20/40 ,  G06N3/044 ,  G06N3/045 ,  G06N3/049 ,  G06T1/20 ,  G06T2200/28 ,  G06T2207/20084

摘要： Methods, systems, and apparatus, including computer programs encoded on computer storage media, for parallel processing of video frames using neural networks. One of the methods includes receiving a video sequence comprising a respective video frame at each of a plurality of time steps; and processing the video sequence using a video processing neural network to generate a video processing output for the video sequence, wherein the video processing neural network includes a sequence of network components, wherein the network components comprise a plurality of layer blocks each comprising one or more neural network layers, wherein each component is active for a respective subset of the plurality of time steps, and wherein each layer block is configured to, at each time step at which the layer block is active, receive an input generated at a previous time step and to process the input to generate a block output.

公开(公告)号：US11966964B2

公开(公告)日：2024-04-23

申请号：US16779535

申请日：2020-01-31

申请人： Walmart Apollo, LLC

发明人： Snehasish Mukherjee ,  Deepa Mohan ,  Haoxuan Chen ,  Phani Ram Sayapaneni ,  Ghodratollah Aalipour Hafshejani ,  Shankara Bhargava Subramanya

IPC分类号： G06Q30/0601 ,  G06F16/22 ,  G06N3/042 ,  G06N3/044 ,  G06N3/08 ,  G10L15/16 ,  G10L15/18 ,  G10L15/22

CPC分类号： G06Q30/0633 ,  G06F16/22 ,  G06N3/042 ,  G06N3/044 ,  G06N3/08 ,  G06Q30/0603 ,  G06Q30/0619 ,  G10L15/16 ,  G10L15/1815 ,  G10L15/22 ,  G10L2015/223

摘要： A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions configured to run on the one or more processors and perform receiving a voice command from a user; transforming the voice command; transforming the voice command can include using a natural language understanding and rules execution engine into (a) an intent of the user to add recipe ingredients to a cart and (b) a recipe descriptor; determining a matching recipe from a set of ingested recipes based on the recipe descriptor; determining items and quantities associated with the items that correspond to a set of ingredients included in the matching recipe using a quantity inference algorithm; and automatically adding all of the items and the quantities associated with the items to the cart. Other embodiments are disclosed.

公开(公告)号：US11966540B2

公开(公告)日：2024-04-23

申请号：US18064114

申请日：2022-12-09

申请人： Microsoft Technology Licensing, LLC

发明人： Yotam Livny ,  Nir David ,  Yael Livne

IPC分类号： G06F3/041 ,  G06N3/044 ,  G06N3/084

CPC分类号： G06F3/0418 ,  G06F3/04166 ,  G06N3/044 ,  G06N3/084

摘要： A computing system includes a touch-sensitive display and one or more processors. The touch-sensitive display is configured to detect a run-time touch input from a user. The one or more processors are configured to execute instructions using portions of associated memory to implement a touch driver of the touch-sensitive display and an artificial intelligence model. The touch driver is configured to process the run-time touch input based on a plurality of calibration parameters and output a touch event and a plurality of run-time touch input parameters associated with the touch input event. The artificial intelligence model is configured to receive, as input, the run-time touch input parameters. Responsive to receiving the run-time touch input parameters, the artificial intelligence model is configured to output a personalized user touch driver profile including a plurality of updated calibration parameters for the touch driver.