Classification Or Recognition Patents (Class 706/20)
  • Patent number: 11461655
    Abstract: A system and method for controlling a nodal network. The method includes estimating an effect on the objective caused by the existence or non-existence of a direct connection between a pair of nodes and changing a structure of the nodal network based at least in part on the estimate of the effect. A nodal network includes a strict partially ordered set, a weighted directed acyclic graph, an artificial neural network, and/or a layered feed-forward neural network.
    Type: Grant
    Filed: January 28, 2019
    Date of Patent: October 4, 2022
    Assignee: D5AI LLC
    Inventors: James K. Baker, Bradley J. Baker
  • Patent number: 11461372
    Abstract: A data clustering device includes an input configured to receive a plurality of data points encoded in at least one signal and a hardware logic circuit configured to extract one or more features of the one or more data points from the at least one signal, create or update, based on the one or more features, one or more data clusters representing one or more of the data points, and encode at least one of the one or more data clusters in at least one output signal. The device further includes an output configured to provide the at least one output signal, for instance, to a processor, such as a processor for controlling a controlled system. The device can be further configured to split or merge the data cluster(s) based on a statistical distribution of the one or more data points in the respective data cluster.
    Type: Grant
    Filed: March 18, 2021
    Date of Patent: October 4, 2022
    Assignee: BAE Systems Information and Electronic Systems Integration Inc.
    Inventors: Sandeep Mishra, James C. Bode, Michael C. Caron, Thomas A. Folsom, Michael A. Zalucki
  • Patent number: 11455517
    Abstract: Anomalies in a data set may be difficult to detect when individual items are not gross outliers from a population average. Disclosed is an anomaly detector that includes neural networks such as an auto-encoder and a discriminator. The auto-encoder and the discriminator may be trained on a training set that does not include anomalies. During training, an auto-encoder generates an internal representation from the training set, and reconstructs the training set from the internal representation. The training continues until data loss in the reconstructed training set is below a configurable threshold. The discriminator may be trained until the internal representation is constrained to a multivariable unit normal. Once trained, the auto-encoder and discriminator identify anomalies in the evaluation set. The identified anomalies in an evaluation set may be linked to transaction, security breach or population trends, but broadly, disclosed techniques can be used to identify anomalies in any suitable population.
    Type: Grant
    Filed: October 26, 2017
    Date of Patent: September 27, 2022
    Assignee: PayPal, Inc.
    Inventors: David Tolpin, Amit Batzir, Nofar Betzalel, Michael Dymshits, Benjamin Hillel Myara, Liron Ben Kimon
  • Patent number: 11450082
    Abstract: In one embodiment, L dimensional images are trained, mapped, and aligned to an M dimensional topology to obtain azimuthal angles. The aligned L dimensional images are then trained and mapped to an N dimensional topology to obtain 2N vertex classifications. The azimuthal angles and the 2N vertex classifications are used to map L dimensional images into 0 dimensional images.
    Type: Grant
    Filed: December 10, 2018
    Date of Patent: September 20, 2022
    Inventor: Christopher L. Kavanau
  • Patent number: 11448570
    Abstract: One embodiment can provide a system for detecting anomaly for high-dimensional sensor data associated with one or more machines. During operation, the system can obtain sensor data from a set of sensor associated with one or machines, apply data exploration techniques on the sensor data to automatically process sensor data to identify a subset of feature sensors from the available set of feature sensors, apply an unsupervised machine-learning technique to the identified subset of feature sensors and the target sensor to learn a set of pair-wise univariate models, and determine whether and how an anomaly occurs in the operation of the one or more machines based on the set of pair-wise univariate models.
    Type: Grant
    Filed: June 4, 2019
    Date of Patent: September 20, 2022
    Assignees: Palo Alto Research Center Incorporated, Panasonic Holdings Corporation
    Inventors: Deokwoo Jung, Fangzhou Cheng, Ajay Raghavan, Yukinori Sasaki, Akira Minegishi, Tetsuyoshi Ogura, Yosuke Tajika
  • Patent number: 11449670
    Abstract: Disclosed are a method, a device, a system and/or a manufacture of iterative development and/or scalable deployment of a spreadsheet-based formula algorithm. In one embodiment, a system for scalable application of a data model defined in a spreadsheet to a dataset includes a translation server and an execution server. The translation server receives a spreadsheet file including a formula algorithm. The formula algorithm includes one or more spreadsheet formulas stored in cells. The translation server generates an extrapolated algorithm expressed in a programming language based on the formula algorithm. The execution server receives the extrapolated algorithm and the dataset and verifies calculation independence when applied to a data entry. The extrapolated algorithm is applied against the dataset. An iteration engine may continuously reapply the extrapolated algorithm to update an output data as the dataset evolves and/or receive an update to the formula algorithm and reapply the extrapolated algorithm.
    Type: Grant
    Filed: December 26, 2020
    Date of Patent: September 20, 2022
    Assignee: ScienceSheet Inc.
    Inventor: Oscar Castañeda-Villagrán
  • Patent number: 11449607
    Abstract: Some examples relate generally to computer architecture software for information security and, in some more particular aspects, to machine learning based on changes in snapshot metadata for anomaly and ransomware detection in a file system.
    Type: Grant
    Filed: August 7, 2019
    Date of Patent: September 20, 2022
    Assignee: Rubrik, Inc.
    Inventors: Oscar Annen, Di Wu, Ajay Saini
  • Patent number: 11449726
    Abstract: A system and method determine a classification by simulating a human user. The system and method translate an input segment such as speech into an output segment such as text and represents the frequency of words and phrases in the textual segment as an input vector. The system and method process the input vector and generate a plurality of intents and a plurality of sub-entities. The processing of multiple intents and sub-entities generates a second multiple of intents and sub-entities that represent a species classification. The system and method select an instance of an evolutionary model as a result of the recognition of one or more predefined semantically relevant words and phrases detected in the input vector.
    Type: Grant
    Filed: July 23, 2020
    Date of Patent: September 20, 2022
    Assignee: PROGRESSIVE CASUALTY INSURANCE COMPANY
    Inventors: Craig S. Sesnowitz, Geoffrey S. McCormack, Rama Rao Panguluri, Robert R. Wagner
  • Patent number: 11443210
    Abstract: A non-transitory computer-readable recording medium stores therein a predicting program that causes a computer to execute: receiving input data to be subjected to prediction; and generating, from training data sets each having explanatory variables and an objective variable, a prediction result, by using a hypothesis set and respective weights of hypotheses included in the hypothesis set, the hypotheses each being formed of a combination of the explanatory variables, classifying any of the training data sets and satisfying a specific condition, the weights being learnt based on whether each of the hypotheses holds true for each of the training data sets. The generating includes determining a value of a variable included in a pseudo-Boolean function such that a probability satisfies a predetermined standard, the probability being a probability that the prediction result satisfies the specific condition, the pseudo-Boolean function including variables corresponding to the explanatory variables.
    Type: Grant
    Filed: June 12, 2020
    Date of Patent: September 13, 2022
    Assignee: FUJITSU LIMITED
    Inventors: Hiroaki Iwashita, Takuya Takagi, Keisuke Goto, Kotaro Ohori
  • Patent number: 11436501
    Abstract: A unique implementation of a machine learning application for suggesting actions for a user to undertake is described herein. The application transforms a history of user behavior into a set of models that represent user actions given a set of parameters. These models are then used to suggest that users in a payments or banking environment take certain actions based on their history. The models are created using the DensiCube, random forest or k-means algorithms.
    Type: Grant
    Filed: August 9, 2019
    Date of Patent: September 6, 2022
    Assignee: Bottomline Technologies, Inc.
    Inventors: Norman DeLuca, Brian McLaughlin, Fred Ramberg, David Sander
  • Patent number: 11436849
    Abstract: Provided herein are systems and methods for applying adaptive classes thresholds to enhance object detection Machine Learning (ML) models by receiving a plurality of labeled feature vectors extracted from a plurality of images associated with a plurality of objects, one or more subsets of the plurality of feature vectors are associated with respective object(s) and labeled accordingly, computing an adaptive threshold for each object in a plurality of iterations, each iteration comprising: (1) computing deviation of a respective feature vector of the subset from an aggregated feature vector, (2) computing, in case the deviation is within a predefined value, a threshold enclosing the respective feature vector, and (3) adjusting the adaptive threshold to enclose the threshold of the respective feature vector and outputting the adaptive threshold(s) for classifying unlabeled feature vectors to class(s) of respective object(s) associated with the adaptive threshold(s) in which the unlabeled feature vectors fall.
    Type: Grant
    Filed: July 20, 2020
    Date of Patent: September 6, 2022
    Assignee: Anyvision Interactive Technologies Ltd.
    Inventors: Alexander Zilberman, Ailon Etshtein, Neil Martin Robertson, Sankha Subhra Mukherjee, Rolf Hugh Baxter, Ishay Sivan, Yaaqov Valero
  • Patent number: 11430259
    Abstract: In implementations of the subject matter described herein, a solution for object detection is proposed. First, a feature(s) is extracted from an image and used to identify a candidate object region in the image. Then another feature(s) is extracted from the identified candidate object region. Based on the features extracted in these two stages, a target object region in the image and a confidence for the target object region are determined. In this way, the features that characterize the image from the whole scale and a local scale are both taken into consideration in object recognition, thereby improving accuracy of the object detection.
    Type: Grant
    Filed: September 26, 2019
    Date of Patent: August 30, 2022
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Dong Chen, Fang Wen, Gang Hua
  • Patent number: 11428803
    Abstract: Disclosed are a method and apparatus for SAR image data enhancement, and a storage medium. The method includes: processing an SAR target image by electromagnetic simulation to acquire an SAR electromagnetic simulation image; and processing the SAR electromagnetic simulation image and the SAR target image by a generative adversarial network to obtain a set of virtual samples of the SAR target image.
    Type: Grant
    Filed: August 2, 2019
    Date of Patent: August 30, 2022
    Assignee: WUYI University
    Inventors: Yikui Zhai, Wenbo Deng, Qirui Ke, Zilu Ying, Junying Gan, Junying Zeng, Ying Xu
  • Patent number: 11429906
    Abstract: A computer-implemented user profiling system includes a human communication retrieval component which, for an entity employing a business process management system, captures communication data in response to a given business process being implemented by the business process management system. A human task monitoring and contextual analysis component captures user behavior information associated with the business process. A profile analysis engine is also included, which receives the user behavior information and communication data and updates a user profile corresponding to at least one of the users, based on the user behavior information and communication data.
    Type: Grant
    Filed: June 16, 2016
    Date of Patent: August 30, 2022
    Assignee: Conduent Business Services, LLC
    Inventors: Kunal Suri, Scott Peter Nowson, Adrian Corneliu Mos
  • Patent number: 11429844
    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a policy neural network used to select actions to be performed by a reinforcement learning agent interacting with an environment. In one aspect, a method includes obtaining path data defining a path through the environment traversed by the agent. A consistency error is determined for the path from a combined reward, first and last soft-max state values, and a path likelihood. A value update for the current values of the policy neural network parameters is determined from at least the consistency error. The value update is used to adjust the current values of the policy neural network parameters.
    Type: Grant
    Filed: June 18, 2020
    Date of Patent: August 30, 2022
    Assignee: Google LLC
    Inventors: Ofir Nachum, Mohammad Norouzi, Dale Eric Schuurmans, Kelvin Xu
  • Patent number: 11429854
    Abstract: A method for training a computerized mechanical device, comprising: receiving data documenting actions of an actuator performing a task in a plurality of iterations; calculating using the data a neural network dataset and used for performing the task; gathering in a plurality of reward iterations a plurality of scores given by an instructor to a plurality of states, each comprising at least one sensor value, while a robotic actuator performs the task according to the neural network; calculating using the plurality of scores a reward dataset used for computing a reward function; updating at least some of the neural network's plurality of parameters by receiving in each of a plurality of policy iterations a reward value computed by applying the reward function to another state comprising at least one sensor value, while the robotic actuator performs the task according to the neural network; and outputting the updated neural network.
    Type: Grant
    Filed: December 4, 2017
    Date of Patent: August 30, 2022
    Assignee: Technion Research & Development Foundation Limited
    Inventors: Ran El-Yaniv, Bar Hilleli
  • Patent number: 11423583
    Abstract: The exemplary embodiments disclose a method, a computer program product, and a computer system for mitigating the risks associated with handling items. The exemplary embodiments may include collecting data relating to one or more items, extracting one or more features from the collected data, determining one or more hazards based on the extracted one or more features and one or more models, and displaying the one or more hazards within an augmented reality device worn by a user.
    Type: Grant
    Filed: July 6, 2020
    Date of Patent: August 23, 2022
    Assignee: International Business Machines Corporation
    Inventors: Shikhar Kwatra, Sarbajit K. Rakshit, Adam Lee Griffin, Spencer Thomas Reynolds
  • Patent number: 11420325
    Abstract: The present disclosure relates to a method, an apparatus and a system for controlling a robot, and a storage medium. The method uses a neural network connected to an external memory to conduct the controlling of the robot, and comprises: inputting input data into the learned neural network to obtain output data, wherein said input data comprises an image about an object, said output data comprises control data about said robot; and establishing an association between part or all of the information generated by said neural network during the calculation and said input data and/or said output data, wherein said part or all of the information represents a feature of said object related to said control data. Thus, the user can grasp the calculation process of the neural network.
    Type: Grant
    Filed: March 5, 2018
    Date of Patent: August 23, 2022
    Assignee: OMRON Corporation
    Inventor: Yoshihisa Ijiri
  • Patent number: 11423303
    Abstract: Apparatus and associated methods relate to providing a machine learning methodology that uses the machine learning's own failure experiences to optimize future solution search and provide self-guided information (e.g., the dependency and independency among various adaptation behavior) to predict a receiver's equalization adaptations. In an illustrative example, a method may include performing a first training on a first neural network model and determining whether all of the equalization parameters are tracked. If not all of the equalization parameters are tracked under the first training, then, a second training on a cascaded model may be performed. The cascaded model may include the first neural network model, and training data of the second training may include successful learning experiences and data of the first neural network model. The prediction accuracy of the trained model may be advantageously kept while having a low demand for training data.
    Type: Grant
    Filed: November 21, 2019
    Date of Patent: August 23, 2022
    Assignee: XILINX, INC.
    Inventors: Shuo Jiao, Romi Mayder, Bowen Li, Geoffrey Zhang
  • Patent number: 11416738
    Abstract: Techniques for model reutilization with heterogeneous sensor stacks via sensor data auto-normalization are described. A normalization model can be trained and utilized to normalize sensor data generated by a first type of sensor stack so that it can be used with an existing machine learning model that was trained using data from another type or types of sensor stacks having different characteristics. A sensor data can be generated by the sensor stack and provided as an input to the normalization model to yield normalized sensor data. The normalized sensor data can be provided as input to the existing model to generate accurate results despite the sensor stack having different characteristics than the one(s) used to train the machine learning model.
    Type: Grant
    Filed: November 21, 2017
    Date of Patent: August 16, 2022
    Assignee: Amazon Technologies, Inc.
    Inventor: Aran Khanna
  • Patent number: 11409925
    Abstract: This disclosure relates to methods and systems for simulation of electricity value ecosystem using agent based modeling approach. State-of-the-art methods utilize simulation tools to support decision making that do not model agents own behaviour and its response to other agents based on an interaction, thereby unable to analyse complex interactions in the electricity value ecosystem. The present disclosure provides a generalized integrated simulation platform which provides dynamic configurability to simulate a plurality of user requirements associated with the electricity value eco-system using a causal diagram which is further used to identify a plurality of agents. Further, a plurality of a plurality of models and processes for the plurality of agents are determined or generated based on their availability in a repository. The causal diagram is refined in accordance with one or more constraints which supports in making a better and informed decision considering changing dynamics of the plurality of agents.
    Type: Grant
    Filed: April 8, 2020
    Date of Patent: August 9, 2022
    Assignee: Tata Consultancy Services Limited
    Inventors: Yogesh Kumar Bichpuriya, Venkatesh Sarangan, Sivaramakrishnan Chandrasekaran, Narayanan Rajagopal, Nilesh Sadashiv Hiremath, Vinodhkanna Jayaraman
  • Patent number: 11409769
    Abstract: A system and method for attribute discovery for operation objects from operation data includes segmenting a name of each of a plurality of operation objects based on one or more special characters used in the name of each operation object. A similarity comparison of the operation objects is performed by extracting common subsequences from substrings in operation data in a same log as a target object, and a string similarity is computed of the extracted common subsequences. Numerical attributes are determined by calculating statistical metrics for fields in the log, and additional information of the operation objects is discovered based on the determined numerical attributes.
    Type: Grant
    Filed: March 15, 2020
    Date of Patent: August 9, 2022
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Jia Qi Li, Fan Jing Meng, Jing Min Xu, Zi Xiao Zhu
  • Patent number: 11410449
    Abstract: This disclosure relates to improved techniques for performing human parsing functions using neural network architectures. The neural network architecture can model human objects in images using a hierarchal graph of interconnected nodes that correspond to anatomical features at various levels. Multi-level inference information can be generated for each of the nodes using separate inference processes. The multi-level inference information for each node can be combined or fused to generate final predictions for each of the nodes. Parsing results may be generated based on the final predictions.
    Type: Grant
    Filed: October 17, 2019
    Date of Patent: August 9, 2022
    Assignee: Inception Institute of Artificial Intelligence, Ltd.
    Inventors: Wenguan Wang, Jianbing Shen, Zhijie Zhang, Ling Shao
  • Patent number: 11396244
    Abstract: Methods and systems for communicating with a server of a cloud services system used to interface with vehicles are provided. One method includes receiving, by the server, a request from electronics of a vehicle to access a profile for a user account. The request identifies user information for a user to use the vehicle. The method includes processing, by the server, at least part of the user information to verify the user against data associated with the user account. The profile has a plurality of settings of the user for the vehicle, and at least part of the plurality of settings for the profile being stored on storage accessible to the cloud services system. The method includes transferring, by the server, upon verification of the user information, one or more settings of the plurality of settings to the vehicle.
    Type: Grant
    Filed: February 11, 2020
    Date of Patent: July 26, 2022
    Assignee: Emerging Automotive, LLC
    Inventors: Angel A. Penilla, Albert S. Penilla
  • Patent number: 11397888
    Abstract: A virtual agent with a dialogue management system and a method of training the dialogue management system is disclosed. The dialogue management system is trained using a deep reinforcement learning process. Training involves obtaining or simulating training dialogue data. During the training process, actions for the dialogue management system are selected using a Deep Q Network to process observations. The Deep Q Network is updated using a target function that includes a reward. The reward may be generated by considering one or more of the following metrics: task completion percentage, dialogue length, sentiment analysis of the user's response, emotional analysis of the user's state, explicit user feedback, and assessed quality of the action. The set of actions that the dialogue management system can take at any time may be limited by an action screener that predicts the subset of actions that the agent should consider for a given state of the system.
    Type: Grant
    Filed: June 14, 2018
    Date of Patent: July 26, 2022
    Assignee: Accenture Global Solutions Limited
    Inventors: Harshawardhan Madhukar Wabgaonkar, Shubhashis Sengupta, Tulika Saha
  • Patent number: 11390286
    Abstract: A system for end to end prediction of lane detection uncertainty includes a sensor device of a host vehicle generating data related to a road surface and a navigation controller including a computerized processor operable to monitor an input image from the sensor device, utilize a convolutional neural network to analyze the input image and output a lane prediction and a lane uncertainty prediction, and generate a commanded navigation plot based upon the lane prediction and the lane uncertainty prediction. The convolutional neural network is initially trained using a per point association and error calculation, including associating a selected ground truth lane to a selected set of data points related to a predicted lane and then associating at least one point of the selected ground truth lane to a corresponding data point from the selected set of data points related to the predicted lane.
    Type: Grant
    Filed: March 4, 2020
    Date of Patent: July 19, 2022
    Assignee: GM Global Technology Operations LLC
    Inventors: Netalee Efrat Sela, Max Bluvstein, Bat El Shlomo
  • Patent number: 11386327
    Abstract: Embodiments for training a neural network are provided. A neural network is divided into a first block and a second block, and the parameters in the first block and second block are trained in parallel. To train the parameters, a gradient from a gradient mini-batch included in training data is generated. A curvature-vector product from a curvature mini-batch included in the training data is also generated. The gradient and the curvature-vector product generate a conjugate gradient. The conjugate gradient is used to determine a change in parameters in the first block in parallel with a change in parameters in the second block. The curvature matrix in the curvature-vector product includes zero values when the terms correspond to parameters from different blocks.
    Type: Grant
    Filed: May 18, 2018
    Date of Patent: July 12, 2022
    Assignee: Salesforce.com, inc.
    Inventors: Huishuai Zhang, Caiming Xiong
  • Patent number: 11385633
    Abstract: Techniques are provided herein for creating well-balanced computer-based reasoning systems and using those to control systems. The techniques include receiving a request to determine whether to use one or more particular data elements, features, cases, etc. in a computer-based reasoning model (e.g., as data elements, cases or features are being added, or as part of pruning existing features or cases). Conviction measures are determined and inclusivity conditions are tested. The result of comparing the conviction measure can be used to determine whether to include or exclude the feature, case, etc. in the model and/or whether there are anomalies in the model. A controllable system may then be controlled using the computer-based reasoning model.
    Type: Grant
    Filed: August 13, 2020
    Date of Patent: July 12, 2022
    Assignee: Diveplane Corporation
    Inventors: Christopher James Hazard, Michael Resnick, Ravisutha Sakrepatna Srinivasamurthy, David R. Cheeseman, Ju Hyun Kim, Yamac Alican Isik
  • Patent number: 11386567
    Abstract: System, methods, and other embodiments described herein relate to semi-supervised training of a depth model for monocular depth estimation. In one embodiment, a method includes training the depth model according to a first stage that is self-supervised and that includes using first training data that comprises pairs of training images. Respective ones of the pairs including separate frames depicting a scene of a monocular video. The method includes training the depth model according to a second stage that is weakly supervised and that includes using second training data to produce depth maps according to the depth model. The second training data comprising individual images with corresponding sparse depth data. The second training data providing for updating the depth model according to second stage loss values that are based, at least in part, on the depth maps and the depth data.
    Type: Grant
    Filed: December 3, 2019
    Date of Patent: July 12, 2022
    Assignee: Toyota Research Institute, Inc.
    Inventors: Vitor Guizilini, Sudeep Pillai, Rares A. Ambrus, Jie Li, Adrien David Gaidon
  • Patent number: 11388211
    Abstract: A data stream processing system can receive a stream of data and display a portion of the stream to a user. The displayed streaming data can change over time as additional data is received as part of the stream. The data stream processing system can extract one or more field values rom data in the stream and generate filters based on the extracted information. The generated filters can be displayed to a user, and in response to an interaction with a generated filter, the data stream processing system can apply the selected filter to data in the data stream.
    Type: Grant
    Filed: October 16, 2020
    Date of Patent: July 12, 2022
    Assignee: Splunk Inc.
    Inventors: Jared Breeden, Steven Karis, Brian Krueger, Sarah Matarese, Hema Krishnamurthy Mohan, Amin Moshgabadi, Erik Oscar Riiska, Siri Singamneni, Joshua Vertes
  • Patent number: 11379991
    Abstract: A method for digital image segmentation is provided. The method comprises training a neural network for image segmentation with a labeled training dataset from a first domain, wherein a subset of nodes in the neural net are dropped out during training. The neural network receives image data from a second, different domain. A vector of N values that sum to 1 is calculated for each image element, wherein each value represents an image segmentation class. A label is assigned to each image element according to the class with the highest value in the vector. Multiple inferences are performed with active dropout layers for each image element, and an uncertainty value is generated for each image element. The label of any image element with an uncertainty value above a predefined threshold is replaced with a new label corresponding to the class with the next highest value.
    Type: Grant
    Filed: May 29, 2020
    Date of Patent: July 5, 2022
    Assignee: National Technology & Engineering Solutions of Sandia, LLC
    Inventors: Carianne Martinez, Kevin Matthew Potter, Emily Donahue, Matthew David Smith, Charles J. Snider, John P. Korbin, Scott Alan Roberts, Lincoln Collins
  • Patent number: 11361187
    Abstract: Aspects of the subject matter disclosed herein include methods, systems, and other techniques for training, in a first phase, an object classifier neural network with a first set of training data, the first set of training data including a first plurality of training examples, each training example in the first set of training data being labeled with a coarse-object classification; and training, in a second phase after completion of the first phase, the object classifier neural network with a second set of training data, the second set of training data including a second plurality of training examples, each training example in the second set of training data being labeled with a fine-object classification.
    Type: Grant
    Filed: December 11, 2020
    Date of Patent: June 14, 2022
    Assignee: Waymo LLC
    Inventors: Junhua Mao, Congcong Li, Yang Song
  • Patent number: 11361463
    Abstract: Provided is a computer system for estimating an absolute position of a photographed object by just photographing the object with a camera, a position estimation method, and a program. The computer system acquires an image obtained by photographing an object, acquires three-dimensional position data of a camera which photographed the object, and estimates an absolute position of the object on the basis of the three-dimensional position data of the camera. Further, the computer system enables the camera to be tilted a specified angle in a direction of the object, and estimates the absolute position of the object on the basis of the three-dimensional position data of the camera and the tilted specified angle. Moreover, the computer system stores the position of the object and an altitude at the position in association with each other, and estimates an altitude associated with the estimated position of the object.
    Type: Grant
    Filed: September 28, 2017
    Date of Patent: June 14, 2022
    Assignee: OPTIM CORPORATION
    Inventor: Shunji Sugaya
  • Patent number: 11361254
    Abstract: A computerized-system and method for generating a reduced-size superior labeled training-dataset for a high-accuracy machine-learning-classification model for extreme class imbalance by: (a) retrieving minority and majority class instances to mark them as related to an initial dataset; (b) retrieving a sample of majority instances; (c) selecting an instance to operate a clustering classification model on it and the instances marked as related to the initial dataset to yield clusters; (d) operating a learner model to: (i) measure each instance in the yielded clusters according to a differentiability and an indicativeness estimators; (ii) mark measured instances as related to an intermediate training dataset according to the differentiability and the indicativeness estimators; (e) repeating until a preconfigured condition is met; (f) applying a variation estimator on all marked instances as related to an intermediate training dataset to select most distant instances; and (g) marking the instances as related to
    Type: Grant
    Filed: February 24, 2020
    Date of Patent: June 14, 2022
    Assignee: ACTIMIZE LTD
    Inventors: Danny Butvinik, Yoav Avneon
  • Patent number: 11361849
    Abstract: Individual computer diagnostic support (CDS) systems are coupled to a ‘global’ CDS system, each of the CDS systems using the same learning system or the same learning system technique. Training and testing cases from each of the individual CDS systems are provided to the global CDS system, and the global CDS system uses these training cases to produce learning system parameters based on the training cases. Having more training cases than any of the individual CDS systems, the parameters provided by the global CDS system offer a higher quality diagnostic output than any of the individual CDS systems. The learning system parameters at the global CDS system may be provided to each of the individual CDS systems, to update the parameters of the individual CDS systems' learning system. The global CDS may also refine and/or adjust the structure of the embodied learning systems.
    Type: Grant
    Filed: November 10, 2014
    Date of Patent: June 14, 2022
    Assignee: KONINKLIJKE PHILIPS N.V.
    Inventors: Yinhui Deng, Xiaomin Li, Xiaolin Gu, Vijay Thakur Shamdasani, Ying Wu
  • Patent number: 11358061
    Abstract: Disclosed is a non-transitory computer readable medium storing computer program, in which when the computer program is executed by one or more processors. When the computer program is executed by one or more processors of a computing device, the computer program performs an operation for user drawing-based security authentication, and the operations may include: determining to transmit a first control signal to cause a user terminal to display a first drawing input display, which includes one or more subjects, if a lock display release signal is received from the user terminal; receiving a first drawing input information inputted in accordance with the first drawing input display from the user terminal; and determining whether to release the lock display of the user terminal by inputting the received first drawing input information to a drawing evaluation model.
    Type: Grant
    Filed: April 14, 2020
    Date of Patent: June 14, 2022
    Assignee: Netmarble Corporation
    Inventors: Young Soo Kim, Young Bak Jo, Yeongtae Hwang
  • Patent number: 11344818
    Abstract: A computer system, a game loading method thereof and a computer readable storage medium are provided. The computer system includes a first storage, a second storage and a processor. The first storage stores multiple game files of a game. The access rate of the second storage is faster than the first storage. The processor is coupled to the first and second storages. The processor performs the game, stores corresponding game files in the first storage into the second storage according to process of the game, and access the game files stored in the second storage to continue progress of the game. Accordingly, loading time of game scene can be reduced, so as to improve gaming experience.
    Type: Grant
    Filed: April 28, 2019
    Date of Patent: May 31, 2022
    Assignee: Acer Incorporated
    Inventors: Guan-Yu Hou, Tz-Yu Fu, Wei-Kuo Shih
  • Patent number: 11342061
    Abstract: An emotional wellness management system and methods of managing emotional wellness, to help people interactively and iteratively manage and improve their daily processes of emotional wellness. The system comprises storage coupled to a controller for capturing, storing, retrieving, processing, updating and displaying information related to a user's psychological condition comprising user affects, influencers, and actions. A user interface device, coupled to the controller, configured to have a plurality of interactive interfaces to capture user inputs of states of user affects and influencers, provides action links for accessing resources in the user interface device, also providing visual feedback. The controller is configured to interface with at least one controller from a support network via a communication link, and able to capture, store, retrieve, process, update and display information related to user's psychological condition.
    Type: Grant
    Filed: October 19, 2018
    Date of Patent: May 24, 2022
    Inventor: Satoru Isaka
  • Patent number: 11341866
    Abstract: System, methods, and other embodiments described herein relate to improving the training of a driver during automated driving system mode. In one embodiment, a method includes generating, in association with a vehicle takeover and a maneuver by the driver, an automated motion plan associated with the maneuver. The method also includes determining if a difference parameter satisfies a threshold, wherein the difference parameter indicates a disparity between the maneuver by the driver in relation to the automated motion plan associated with the maneuver. The method also includes notifying, if the difference parameter does not satisfy the threshold, the driver that the vehicle takeover and the maneuver by the driver were unnecessary.
    Type: Grant
    Filed: June 30, 2020
    Date of Patent: May 24, 2022
    Assignee: Toyota Research Institute, Inc.
    Inventors: Hiromitsu Urano, Kentaro Ichikawa, Junya Ueno
  • Patent number: 11341626
    Abstract: Embodiments of the present disclosure relate to a method and apparatus for outputting information. The method can include: acquiring an image of a to-be-inspected object; segmenting the image into at least one subimage; for a subimage in the at least one subimage, inputting the subimage into a pre-trained defect classification model to obtain a defect category corresponding to the subimage; and outputting defect information of the object based on a defect category corresponding to each subimage.
    Type: Grant
    Filed: October 28, 2019
    Date of Patent: May 24, 2022
    Assignee: Beijing Baidu Netcom Science and Technology Co., Ltd.
    Inventors: Yawei Wen, Jiabing Leng, Chengcheng Wang, Ye Su, Minghao Liu, Yulin Xu, Jiangliang Guo, Xu Li
  • Patent number: 11341424
    Abstract: In response to receiving observed data of mixed observed variables, a mixed causality objective function, being suitable for continuous observed variables and discrete observed variables is determined, wherein the mixed causality objective function includes a causality objective function for continuous observed variables and a causality objective function for discrete observed variables and the fitting inconsistency is adjusted based on weighted factors of the observed variables. Then, the mixed causality objective function is optimally solved by using a mixed sparse causal inference, suitable for both continuous observed variables and discrete observed variables, using the mixed observed data under a constraint of a directed acyclic graph, to estimate causality among the observed variables.
    Type: Grant
    Filed: December 14, 2018
    Date of Patent: May 24, 2022
    Assignee: NEC CORPORATION
    Inventors: Wenjuan Wei, Chunchen Liu, Lu Feng
  • Patent number: 11335466
    Abstract: A method and apparatus are provided that includes iteratively sampling candidates from medical records and evaluating whether ones of the candidates better explain a member from the medical records. The iterations replace the member with the candidates and depending on whether the candidates better explain the member from the medical records may be weighted in a next iteration.
    Type: Grant
    Filed: February 15, 2019
    Date of Patent: May 17, 2022
    Assignee: TENCENT AMERICA LLC
    Inventors: Yusheng Xie, Tao Yang, Min Tu, Nan Du, Shih-Yao Lin, Wei Fan
  • Patent number: 11334757
    Abstract: Methods and apparatus, including computer program products, implementing and using techniques for processing suspect duplicate records in a master data management system. A master data management module identifies two or more suspect duplicate records in the master data management system based on scores. A matching engine classifies the two or more suspect duplicate records, by comparing the scores against threshold values, into one of: a match, a non-match, and a possible match. The master data management module re-classifies the suspect duplicate records and adjusting the threshold values of the matching engine for classification of future records, in response to receiving, by a data stewardship client, a user input indicating an incorrect classification of the suspect duplicate records.
    Type: Grant
    Filed: June 11, 2018
    Date of Patent: May 17, 2022
    Assignee: International Business Machines Corporation
    Inventors: Sushain Pandit, Martin Oberhofer, Joerg Rehr, Ivan M. Milman
  • Patent number: 11328126
    Abstract: A method, system, and non-transitory compute readable medium determining and discerning items with multiple meanings in a sequence of items including producing a distributed representation for each item of the sequence of items including a word vector and a context vector, partitioning the sequence of items into classes, for an item using a representative word vector of each class, calculating a cosine distance between the word vector of said item and the class representative vector, and producing a new sequence of items by modifying the distributed representation in the producing by replacing each occurrence of an item depending on the cosine distance calculated by the calculating.
    Type: Grant
    Filed: November 21, 2019
    Date of Patent: May 10, 2022
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventor: Oded Shmueli
  • Patent number: 11321464
    Abstract: This disclosure relates to method and system for generating cognitive security intelligence for detecting and preventing malwares. In one embodiment, the method includes monitoring instructions being executed by a processor of a computing system, determining events triggered and activities performed by the execution of the instructions, correlating the events and the activities to determine a sequence of events and activities, and mapping the sequence of events and activities with a topographical threat map to detect a pattern match corresponding to a malware. The topographical threat map is event and activity behavior map of a number of categories of malwares, and is built based on a cognitive analysis using deep learning which may also be enriched with external knowledge or historic knowledge. The method further includes effecting a remedial measure, upon detecting the pattern match, to prevent the malware by constructing remedial instructions to be executed by the processor.
    Type: Grant
    Filed: February 6, 2018
    Date of Patent: May 3, 2022
    Assignee: Wipro Limited
    Inventor: Sridhar Govardhan
  • Patent number: 11321611
    Abstract: Authenticity of Artificial Intelligence (AI) results may be verified by creating, for an AI system, from a plurality of original inputs to form a plurality of original inference results, a plurality of original signatures of representative elements of an internal state of the AI system constructed from each individual original inference result of the plurality of original inference results. During deployment of the AI system, a matching of a plurality of deployment time inference results with a plurality of deployment time signatures, to the plurality of original signatures and the plurality of original inference results, may be verified.
    Type: Grant
    Filed: October 3, 2018
    Date of Patent: May 3, 2022
    Assignee: International Business Machines Corporation
    Inventors: Frank Liu, Bishop Brock, Thomas S. Hubregtsen
  • Patent number: 11323773
    Abstract: A system and method for operating a user receiving device includes a first user device having an identifier associated therewith. A mobile user device obtains the identifier and communicates the identifier associated with the first user receiving device to a second user receiving device. The second user receiving device receives and stores the first user profile settings from the first user receiving device and operates with the first user profile settings.
    Type: Grant
    Filed: July 6, 2018
    Date of Patent: May 3, 2022
    Assignee: DIRECTV, LLC
    Inventors: Kuriacose Joseph, Scott D. Casavant, Sean S. Lee, Phillip T. Wang, Christopher Yang, Woei-Shyang Yee, Wesley W. Huie, Gerard V. Talatinian
  • Patent number: 11321341
    Abstract: A method to dynamically analyze measurement data comprising measurement data sets as the measurement data is received and moved to a data warehouse. The program instructions may receive the measurement data and may extract first metadata from the measurement data. The program instructions may then extract and analyze measurement data points in the measurement data to determine if the measurement data points meet a first criteria and generate second metadata in response to determining that the measurement data points meet the first criteria. The program instructions may then provide the measurement data points, the first metadata and the second metadata to a data warehouse for storage. The analysis of the measurement data and creation of new metadata may be performed dynamically as the data is acquired and stored in the data warehouse.
    Type: Grant
    Filed: May 15, 2020
    Date of Patent: May 3, 2022
    Assignee: National Instruments Corporation
    Inventors: Sundeep Chandhoke, Michael S. Watson, Alejandro del Castillo, Daren K. Wilson
  • Patent number: 11315037
    Abstract: There is provided a system for computing a secure statistical classifier, comprising: at least one hardware processor executing a code for: accessing code instructions of an untrained statistical classifier, accessing a training dataset, accessing a plurality of cryptographic keys, creating a plurality of instances of the untrained statistical classifier, creating a plurality of trained sub-classifiers by training each of the plurality of instances of the untrained statistical classifier by iteratively adjusting adjustable classification parameters of the respective instance of the untrained statistical classifier according to a portion of the training data serving as input and a corresponding ground truth label, and at least one unique cryptographic key of the plurality of cryptographic keys, wherein the adjustable classification parameters of each trained sub-classifier have unique values computed according to corresponding at least one unique cryptographic key, and providing the statistical classifier, whe
    Type: Grant
    Filed: March 14, 2019
    Date of Patent: April 26, 2022
    Assignees: NEC Corporation Of America, Bar-Ilan University, NEC Corporation
    Inventors: Jun Furukawa, Joseph Keshet, Kazuma Ohara, Toshinori Araki, Hikaru Tsuchida, Takuma Amada, Kazuya Kakizaki, Shir Aviv-Reuven
  • Patent number: 11315006
    Abstract: A method for inferring patterns in multi-dimensional image data comprises providing a recursive network of sub-networks with a parent feature node and at least two child feature nodes; wherein each sub-network is associated with a distinct subset of the space; configuring nodes of the sub-networks with posterior distribution component; receiving image data feature input at the final child feature nodes; propagating node activation through the network layer hierarchy in a manner consistent with node connections of sub-networks of the network and the posterior prediction of child nodes; and outputting parent feature node selection to an inferred output.
    Type: Grant
    Filed: March 17, 2017
    Date of Patent: April 26, 2022
    Assignee: Vicarious FPC, Inc.
    Inventors: Dileep George, Kenneth Kansky, D. Scott Phoenix, Bhaskara Marthi, Christopher Laan, Wolfgang Lehrach