Patents Issued in April 30, 2020
  • Publication number: 20200134368
    Abstract: A method is provided that includes generating a visual environment for interactive development of a machine learning (ML) model. The method includes accessing observations of data each of which includes values of independent variables and a dependent variable, and performing an interactive exploratory data analysis (EDA) of the values of a set of the independent variables. The method includes performing a feature construction and selection based on the interactive EDA, and in which select independent variables are selected as or transformed into a set of features for use in building a ML model to predict the dependent variable. The method includes building the ML model using a ML algorithm, the set of features, and a training set produced from the set of features and observations of the data. And the method includes outputting the ML model for deployment to predict the dependent variable for additional observations of the data.
    Type: Application
    Filed: October 25, 2018
    Publication date: April 30, 2020
    Inventors: Seema Chopra, Akshata Kishore Moharir, Arvind Sundararaman, Kaustubh Kaluskar
  • Publication number: 20200134369
    Abstract: A method is provided that includes generating a visual environment for interactive development of a machine learning (ML) model. The method includes accessing observations of data each of which includes values of independent variables and a dependent variable. The method includes performing an interactive feature construction and selection in which select independent variables are selected as or transformed into a set of features for use in building a ML model to predict the dependent variable. The method includes building the ML model using a ML algorithm, the set of features, and a training set produced from the set of features and observations of the data. And the method includes outputting the ML model for deployment to predict the dependent variable for additional observations of the data.
    Type: Application
    Filed: October 25, 2018
    Publication date: April 30, 2020
    Inventors: Seema Chopra, Akshata Kishore Moharir, Arvind Sundararaman, Kaustubh Kaluskar
  • Publication number: 20200134370
    Abstract: A method is provided that includes generating a visual environment for interactive development of a machine learning (ML) model. The method includes accessing observations of data each of which includes values of independent variables and a dependent variable, and performing an interactive exploratory data analysis (EDA) of the values of a set of the independent variables. The method includes performing an interactive feature construction and selection based on the interactive EDA, and in which select independent variables are selected as or transformed into a set of features for use in building a ML model to predict the dependent variable. The method includes building the ML model using a ML algorithm, the set of features, and a training set produced from the set of features and observations of the data. And the method includes outputting the ML model for deployment to predict the dependent variable for additional observations of the data.
    Type: Application
    Filed: October 25, 2018
    Publication date: April 30, 2020
    Inventors: Seema Chopra, Akshata Kishore Moharir, Arvind Sundararaman, Kaustubh Kaluskar
  • Publication number: 20200134371
    Abstract: Embodiments of the present disclosure provide systems, methods, and computer-readable media that use machine learning models to enable computing devices to detect and identify cosmetic products in face images. In some embodiments, a model training system may gather training data for building the machine learning models by analyzing face images associated with tagging data. In some embodiments, a recommendation system may be configured to use the machine learning models generated by the model training system to detect products in face images, and to add information based on the detected products to a look data store, and/or to provide recommendations for similar looks from the look data store based on the detected products.
    Type: Application
    Filed: October 25, 2018
    Publication date: April 30, 2020
    Applicant: L'Oreal
    Inventors: Grégoire Charraud, Helga Malaprade, Géraldine Thiebaut, Matthieu Perrot, Robin Kips
  • Publication number: 20200134372
    Abstract: The present invention relates to methods and systems for generating annotated data for training vehicular driver assist (DA) and autonomous driving (AD) active safety (AS) functionalities and the like. More specifically, the present invention relates to methods and systems for the fast estimation of three-dimensional (3-D) bounding boxes and drivable surfaces using LIDAR point clouds and the like. These methods and systems provide fast and accurate annotation cluster pre-proposals on a minimally-supervised or unsupervised basis, segment drivable surfaces/ground planes in a bird's-eye-view (BEV) construct, and provide fast and accurate annotation cluster pre-proposal labels based on the feature-based detection of similar objects in already-annotated frames. The methods and systems minimize the expertise, time, and expense associated with the manual annotation of LIDAR point clouds and the like in the generation of annotated data for training machine learning (ML) algorithms and the like.
    Type: Application
    Filed: October 26, 2018
    Publication date: April 30, 2020
    Inventors: Sohini ROY CHOWDHURY, Srikar MUPPIRISETTY
  • Publication number: 20200134373
    Abstract: A machine learning device includes a state variable acquiring section, a teaching data acquiring section, and a learned model generating section. The state variable acquiring section acquires, as state variables: feature information that is information regarding a feature of an actual printed matter on which printing has been actually performed by an image forming apparatus; medium information that is information regarding a print medium used in the actual printed matter; and first control information that is information regarding control performed when the actual printed matter has been outputted. The teaching data acquiring section acquires, as teaching data, second control information that is information regarding control that causes the feature information to fall within a predetermined threshold. The learned model generating section generates a learned model by performing machine learning on the basis of the pieces of information acquired by the state variable acquiring section and the teaching data.
    Type: Application
    Filed: October 18, 2019
    Publication date: April 30, 2020
    Inventors: Masashi OIKAWA, Kunio KANAI, Atsushi KITAHARA, Toshiaki TAKAMUNE
  • Publication number: 20200134374
    Abstract: Dynamically updating, or retraining and updating, artificial intelligence (AI)/machine learning (ML) models in digital processes at runtime is disclosed. Production operation may not need to be stopped for AI/ML model update or retraining and update. The update steps and/or retraining steps for the AWL model may be included as part of the digital process. The AI/ML model update may be requested from internal logic (e.g., from the evaluation of a condition, by an that expression calls for the AI/ML model, etc.), external requests (e.g., from external triggers in a finite state machine (FSM), such as a file change, database data, a service call, etc.), or both. Automation of AI/ML model updates or retraining and updates may be provided, where the software reloads/reinitializes/re-instantiates with a retrained and/or updated AWL model after (and possibly immediately after) the AI/ML model becomes available.
    Type: Application
    Filed: December 20, 2019
    Publication date: April 30, 2020
    Applicant: UiPath, Inc.
    Inventor: Andrei Robert Oros
  • Publication number: 20200134375
    Abstract: A semantic segmentation model training method includes: performing, by a semantic segmentation model, image semantic segmentation on at least one unlabeled image to obtain a preliminary semantic segmentation result as the category of the unlabeled image; obtaining, by a convolutional neural network based on the category of the at least one unlabeled image and the category of at least one labeled image, sub-images respectively corresponding to the at least two images and features corresponding to the sub-images, where the at least two images comprise the at least one unlabeled image and the at least one labeled image, and the at least two sub-images carry the categories of the corresponding images; and training the semantic segmentation model on the basis of the categories of the at least two sub-images and feature distances between the at least two sub-images.
    Type: Application
    Filed: December 25, 2019
    Publication date: April 30, 2020
    Applicant: BEIJING SENSETIME TECHNOLOGY DEVELOPMENT CO., LTD.
    Inventors: Xiaohang ZHAN, Ziwei LIU, Ping LUO, Chen Change LOY, Xiaoou TANG
  • Publication number: 20200134376
    Abstract: A computer architecture for an and-or neural network is disclosed. A computing machine accesses an input vector. The input vector comprises a numeric representation of an input to a neural network. The computing machine provides the input vector to the neural network comprising a plurality of ordered layers. The plurality of ordered layers are alternating AND-layers and OR-layers. Each of the plurality of ordered layers receives input from a preceding layer and/or provides output to a next layer. The computing machine generates an output of the neural network based on an output of a last one of the plurality of ordered layers in the neural network.
    Type: Application
    Filed: October 25, 2018
    Publication date: April 30, 2020
    Inventor: Philip A. Sallee
  • Publication number: 20200134377
    Abstract: Disclosed herein are techniques for detecting logos in images or video. In one embodiment, a first logo detection model detects, from an image, candidate regions for determining logos in the image. A feature vector is then extracted from each candidate region and is compared with reference feature vectors stored in a database. The logo corresponding to the best matching reference feature vector is determined to be the logo in the candidate region if the best matching meets a certain criterion. In some embodiments, a second logo detection model trained using synthetic training images is used in combination with the first logo detection model to detect logos in a same image.
    Type: Application
    Filed: October 25, 2018
    Publication date: April 30, 2020
    Inventors: Brunno Fidel Maciel Attorre, Nicolas Huynh Thien
  • Publication number: 20200134378
    Abstract: A method is provided for generating training data to facilitate automatically locating an object of interest within an image. Methods may include: receiving sensor data including a plurality of images from at least one image sensor; receiving an identification, from a user, of an object visible within an image of the plurality of images, where at least a portion of the object is visible in one or more of the plurality of images; determining a predicted location of the object in the one or more of the remaining images of the plurality of images; identifying the object in the one or more of the remaining images of the plurality of images; and storing the plurality of images including an indication of the object at the object location within the one or more of the plurality of images.
    Type: Application
    Filed: October 30, 2018
    Publication date: April 30, 2020
    Inventor: Anirudh VISWANATHAN
  • Publication number: 20200134379
    Abstract: Acquiring labeled data can be a significant bottleneck in the development of machine learning models that are accurate and efficient enough to enable safety-critical applications, such as automated driving. The process of labeling of driving logs can be automated. Unlabeled real-world driving logs, which include data captured by one or more vehicle sensors, can be automatically labeled to generate one or more labeled real-world driving logs. The automatic labeling can include analysis-by-synthesis on the unlabeled real-world driving logs to generate simulated driving logs, which can include reconstructed driving scenes or portions thereof. The automatic labeling can further include simulation-to-real automatic labeling on the simulated driving logs and the unlabeled real-world driving logs to generate one or more labeled real-world driving logs. The automatically labeled real-world driving logs can be stored in one or more data stores for subsequent training, validation, evaluation, and/or model management.
    Type: Application
    Filed: October 30, 2018
    Publication date: April 30, 2020
    Inventors: Adrien David Gaidon, James J. Kuffner, JR., Sudeep Pillai
  • Publication number: 20200134380
    Abstract: Disclosed are a method for updating a neural network and an electronic device. The method includes: inputting a first image set having tag information into a first depth neural network, and determining a cross entropy loss value of the first image set by using the first depth neural network; inputting a second image set having no tag information separately into the first depth neural network and a second depth neural network, and determining a consistency loss value of the second image set, the first depth neural network and the second depth neural network having the same network structure; updating parameters of the first depth neural network based on the cross entropy loss value and the consistency loss value; and updating parameters of the second depth neural network based on the updated parameters of the first depth neural network.
    Type: Application
    Filed: October 29, 2019
    Publication date: April 30, 2020
    Inventors: Yonghao XU, Qian ZHANG, Guoli WANG, Chang HUANG
  • Publication number: 20200134381
    Abstract: A method is used in evaluating a test subject in computing environments. A first machine learning system generates test subject features. A second machine learning system analyzes the test subject to detect distinguishing features of the test subject. A third machine learning system performs natural language processing on the test subject features to create evaluation information associated with the test subject. A test subject evaluation system provides an evaluation of the test subject based on the distinguishing features and the evaluation information.
    Type: Application
    Filed: October 29, 2018
    Publication date: April 30, 2020
    Inventors: Venkata Chandra Sekar Rao, Neeraj Kumar Tiwari, Narayan Kulkarni
  • Publication number: 20200134382
    Abstract: Systems and methods for neural network training utilizing specialized loss functions.
    Type: Application
    Filed: November 2, 2018
    Publication date: April 30, 2020
    Inventor: Aleksey Zhuravlev
  • Publication number: 20200134383
    Abstract: An apparatus for training an image generative model and an image generating apparatus are provided. The apparatus generates output images from a plurality of input images based on the generative model, extracts depth features from the respective output images based on a depth classification model, calculates a depth loss from the extracted depth features, and trains the generative model based on an overall loss that includes the calculated depth loss.
    Type: Application
    Filed: October 8, 2019
    Publication date: April 30, 2020
    Applicant: SAMSUNG ELECTRONICS CO., LTD.
    Inventors: Seon Min RHEE, Minsu KO, Jihye KIM, Byung In YOO, Chang Kyu CHOI, Jaejoon HAN
  • Publication number: 20200134384
    Abstract: The learning model building unit (2) builds a learning model for a convolution neural network, by extracting characteristics of abnormality included in a sample image from the convolution neural network using a kernel having a shape corresponding to the shape of the abnormality included in the sample image and by learning the extracted characteristics.
    Type: Application
    Filed: September 14, 2017
    Publication date: April 30, 2020
    Applicant: MITSUBISHI ELECTRIC CORPORATION
    Inventors: Momoyo HINO, Mengxiong WANG, Kazuo SUGIMOTO, Hidetoshi MISHIMA
  • Publication number: 20200134385
    Abstract: Embodiments of this disclosure provide a deep learning model used for image recognition and apparatus and method thereof. The model includes a determination layer configured to determine whether features in feature maps are features of positions where objects of attention are located, and different weights are granted for the positions where the objects of attention are located and other features in performing weight and composition processing on the features. Hence, the model may be guided to be focused on attention features and make correct determination, thereby improving performance and precision of the model.
    Type: Application
    Filed: October 16, 2019
    Publication date: April 30, 2020
    Applicant: FUJITSU LIMITED
    Inventors: Rui YIN, Zhiming TAN
  • Publication number: 20200134386
    Abstract: An image classification apparatus includes an image segmentation module configured to segment a learning image into a plurality of segment images, a primary classification module configured to perform machine learning on a primary classifier using the plurality of segment images, and a secondary classification module configured to calculate a weight value combination for creating a secondary classification estimation value for the learning image from a plurality of primary classification estimation values generated by passing the plurality of segment images to the trained primary classifier, or a machine learning-based learning parameter.
    Type: Application
    Filed: October 24, 2019
    Publication date: April 30, 2020
    Inventors: JoonHo Lee, HyoSeob Song, JiEun Song
  • Publication number: 20200134387
    Abstract: Certain aspects involve evaluating modeling algorithms whose outputs can impact machine-implemented operating environments. For instance, a computing system generates, from a comparison of a set of estimated attribute values of an attribute to a set of validation attribute values of the attribute, a discretized evaluation dataset with data values in multiple categories. The computing system computes, for a modeling algorithm used to generate the estimated attribute values, an evaluation metric. The computing system provides a host computing system with access to the evaluation metric, one or more modeling outputs generated with the modeling algorithm, or both. Providing one or more of these outputs to the host computing system can facilitate modifying one or more machine-implemented operations.
    Type: Application
    Filed: October 31, 2019
    Publication date: April 30, 2020
    Inventors: Lefei LIU, Peter LIU, Jiawei LIU, Peter GAO, Vickey CHANG
  • Publication number: 20200134388
    Abstract: Techniques are disclosed relating to refining, based on user feedback, one or more machine learning engines for automatically generating component-based user interfaces. In various embodiments, a computer system stores template information that defines a plurality of component types and one or more display parameters identified for one or more user interfaces. The computer system may receive a request to generate a user interface, where the request specifies a data set to be displayed. Further, the computer system may automatically generate a user interface, where the generating is performed by one or more machine learning engines that use the template information and the data set as inputs. The computer system may then provide the user interface to one or more users, receive user feedback associated with the user interface, and train at least one of the one or more machine learning engines based on the user feedback.
    Type: Application
    Filed: October 31, 2018
    Publication date: April 30, 2020
    Inventor: Sonke Rohde
  • Publication number: 20200134389
    Abstract: A method for correcting rolling shutter (RS) effects is presented. The method includes generating a plurality of images from a camera, synthesizing RS images from global shutter (GS) counterparts to generate training data to train the structure-and-motion-aware convolutional neural network (CNN), and predicting an RS camera motion and an RS depth map from a single RS image by employing a structure-and-motion-aware CNN to remove RS distortions from the single RS image.
    Type: Application
    Filed: October 4, 2019
    Publication date: April 30, 2020
    Inventors: Quoc-Huy Tran, Bingbing Zhuang, Pan Ji, Manmohan Chandraker
  • Publication number: 20200134390
    Abstract: A method for implementing artificial intelligence agents to perform machine learning tasks using predictive analytics to leverage ensemble policies for maximizing long-term returns includes obtaining a set of inputs including a set of ensemble policies and a meta-policy parameter, selecting an action for execution within the system environment using a meta-policy function determined based in part on the set of ensemble policies and the meta-policy function parameter, causing the artificial intelligence agent to execute the selected action within the system environment, and updating the meta-policy function parameter based on the execution of the selected action.
    Type: Application
    Filed: October 30, 2018
    Publication date: April 30, 2020
    Inventors: Tetsuro Morimura, Hiroki Yanagisawa, Toshiro Takase, Akira Koseki
  • Publication number: 20200134391
    Abstract: A method and data processing system for detecting tampering of a machine learning model is provided. The method includes training a machine learning model. During a training operating period, a plurality of input values is provided to the machine learning model. In response to a predetermined invalid input value, the machine learning model is trained that a predetermined output value will be expected. The model is verified that it has not been tampered with by inputting the predetermined invalid input value during an inference operating period. If the expected output value is provided by the machine learning model in response to the predetermined input value, then the machine learning model has not been tampered with. If the expected output value is not provided, then the machine learning model has been tampered with. The method may be implemented using the data processing system.
    Type: Application
    Filed: October 24, 2018
    Publication date: April 30, 2020
    Inventors: FARIBORZ ASSADERAGHI, MARC JOYE
  • Publication number: 20200134392
    Abstract: In some embodiments, the system is programmed to build from multiple training sets multiple digital models, each for recognizing plant diseases having symptoms of similar sizes. Each digital model can be implemented with a deep learning architecture that classifies an image into one of several classes. For each training set, the system is thus programmed to collect images showing symptoms of one or more plant diseases having similar sizes. These images are then assigned to multiple disease classes. For a first one of the training sets used to build the first digital model, the system is programmed to also include images that correspond to a healthy condition and images of symptoms having other sizes. These images are then assigned to a no-disease class and a catch-all class. Given a new image from a user device, the system is programmed to then first apply the first digital model.
    Type: Application
    Filed: October 23, 2019
    Publication date: April 30, 2020
    Inventors: YICHUAN GUI, WEI GUAN
  • Publication number: 20200134393
    Abstract: Provided is a neural-network-based classification method, including: generating, by a neural network, one or more score vectors corresponding to one or more samples respectively; determining a first subset of the one or more samples according to the one or more score vectors and a first decision threshold, wherein the first subset is associated with a first class; and selecting samples to be re-examined from the one or more samples according to the first subset.
    Type: Application
    Filed: December 17, 2018
    Publication date: April 30, 2020
    Applicant: Industrial Technology Research Institute
    Inventors: Ching-Hao Lai, Mao-Yu Huang
  • Publication number: 20200134394
    Abstract: An information handling system operating a sensor fusion prediction based automatic adjustment system may comprise sensors measuring influencing attributes comprising information handling system operational values, wherein a subset of the influencing attributes influence one of a plurality of system characteristics, and a memory storing definitions of a user behavior characteristic, a performance mapping characteristic, a power status characteristic, a security profile characteristic, and a policy configuration characteristic.
    Type: Application
    Filed: October 26, 2018
    Publication date: April 30, 2020
    Applicant: Dell Products, LP
    Inventors: Abeye Teshome, Sinem Gulbay
  • Publication number: 20200134395
    Abstract: A system and method for combining computer vision information about human subjects within the field-of-view of a computer vision subsystem with RF Angle of Arrival (AoA) information from an RF receiver subsystem to locate, identify, and track individuals and their location. The RF receiver subsystem may receive RF signals emitted by one or more electronic devices (e.g., a mobile phone) carried, held, or otherwise associated with am individual. Further, gestures can be made with the device and they can be detected by the system.
    Type: Application
    Filed: October 30, 2018
    Publication date: April 30, 2020
    Inventors: CHOUCHANG YANG, ALANSON SAMPLE
  • Publication number: 20200134396
    Abstract: An apparatus includes a primary surround view camera, a supplementary camera, a detection and ranging sensor, and a surround view display. The primary surround view camera is generally placed at a front of a vehicle and provides an operator of the vehicle with a view of the road. The at least one detection and ranging sensor is generally mounted adjacent to the supplementary camera and configured to detect obstacles within a field of view of the supplementary camera. An output of the primary surround view camera is generally used to produce a two-dimensional view of an area around the vehicle and an output of the supplementary camera is (i) reduced to a portion of the field of view of the supplementary camera in which the detection and ranging sensor detected an obstacle and (ii) overlaid on the two-dimensional view of the area around the vehicle to inform the operator of the detected obstacle.
    Type: Application
    Filed: April 18, 2019
    Publication date: April 30, 2020
    Inventor: Pier Paolo Porta
  • Publication number: 20200134397
    Abstract: A method and an electronic device are disclosed. The method includes obtaining an image, obtaining information of the image, obtaining content information of content included in the image, obtaining related information which relates to the image based on at least one of the information of the image and the content information, and classifying the image into at least one category based on a plurality of defined information/data elements and a relation among the information/data elements and metadata of the image.
    Type: Application
    Filed: December 26, 2019
    Publication date: April 30, 2020
    Inventors: Woo-Chan KIM, Jun-Seok HEO
  • Publication number: 20200134398
    Abstract: Inferring multimodal content intent in a common geometric space in order to improve recognition of influential impacts of content includes mapping the multimodal content in a common geometric space by embedding a multimodal feature vector representing a first modality of the multimodal content and a second modality of the multimodal content and inferring intent of the multimodal content mapped into the common geometric space such that connections between multimodal content result in an improvement in recognition of the influential impact of the multimodal content.
    Type: Application
    Filed: April 12, 2019
    Publication date: April 30, 2020
    Inventors: Julia Kruk, Jonah M. Lubin, Karan Sikka, Xiao Lin, Ajay Divakaran
  • Publication number: 20200134399
    Abstract: Systems, computer-implemented methods, and computer program products for transforming a source distribution to a target distribution. A system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise a sampling component that receives a source distribution having a source sample and a target distribution having a target sample. The computer executable components can further comprise an optimizer component that employs a neural network to find a critic that dynamically discriminates between the source sample and the target sample, while constraining a gradient of the neural network. The computer executable components can further comprise a morphing component that generates a first product distribution by morphing the source distribution along the gradient of the neural network to the target distribution.
    Type: Application
    Filed: October 30, 2018
    Publication date: April 30, 2020
    Inventors: Youssef Mroueh, Tom Sercu
  • Publication number: 20200134400
    Abstract: A computer-implemented method includes obtaining a trained convolutional neural network comprising one or more convolutional layers, each of the one or more convolutional layers comprising a plurality of filters with known filter parameters; pre-computing a reusable factor for each of the one or more convolutional layers based on the known filter parameters of the trained convolutional neural network; receiving input data to the trained convolutional neural network; computing an output of the each of the one or more convolutional layers using a Winograd convolutional operator based on the pre-computed reusable factor and the input data; and determining output data of the trained convolutional network based on the output of the each of the one or more convolutional layers.
    Type: Application
    Filed: April 22, 2019
    Publication date: April 30, 2020
    Applicant: Alibaba Group Holding Limited
    Inventors: Yongchao Liu, Qiyin Huang, Guozhen Pan, Sizhong Li, Jianguo Xu, Haitao Zhang, Lin Wang
  • Publication number: 20200134401
    Abstract: A web detection system processes webpage information and performs automated feature extraction of webpages including machine processable information. In an embodiment, the web detection system determines a subset of webpages having a target characteristic by processing markup language. For a webpage of the subset, the web detection system determines that a first image overlaps at least a portion of a second image in the webpage. The web detection system generates an image of the webpage such that the portion of the second image is obscured by the first image. The web detection system determines a graphical feature of the webpage by processing the image, e.g., using optical character recognition. Responsive to determining that the graphical feature corresponds to graphical features of images of a different set of webpages associated with a target entity, the web detection system determines that the webpage is also associated with the target entity.
    Type: Application
    Filed: October 26, 2018
    Publication date: April 30, 2020
    Inventors: David B. Hurry, David J. Tabacco
  • Publication number: 20200134402
    Abstract: In processing to thicken a white thin line, the application range thereof is controlled to as to prevent a white thin line not intended by a user from being thickened. The thickening processing is performed for a line that has a density less than or equal to a predetermined density and includes a pixel having attribute information of a drawing object; and not performed for a line that has a density less than or equal to the predetermined density and includes a pixel not having attribute information of the drawing object.
    Type: Application
    Filed: October 10, 2019
    Publication date: April 30, 2020
    Inventor: Takashi Yabe
  • Publication number: 20200134403
    Abstract: In conventional color shading (CS) processing for correcting color unevenness with high precision, even an image to preserve pure colors can be corrected to use inks of other colors. Color unevenness is more appropriately corrected to provide a favorable image by properly using pure color preservation information and pure color non-preservation information as color correction information for the CS processing.
    Type: Application
    Filed: October 18, 2019
    Publication date: April 30, 2020
    Inventor: Minako Kato
  • Publication number: 20200134404
    Abstract: In an example method, a dot pattern of pixels including information to be encoded across an image is mapped to a corresponding subset of the grayscale source pixels corresponding to the image to be printed. A value of a grayscale pixel in the subset of the grayscale source pixels is modified based on based on a predetermined threshold pixel value. The value of the grayscale pixel is decreased in response to detecting that the predetermined threshold pixel value is exceeded. The clipping channel color is used to detect the dot pattern of pixels. The image including the subset of pixels with modified values is printed.
    Type: Application
    Filed: June 15, 2018
    Publication date: April 30, 2020
    Inventors: Robert Ulichney, Matthew D. Gaubatz
  • Publication number: 20200134405
    Abstract: Described herein are methods and devices for printing a large-size object on multiple sheets. The method includes receiving, at a printing device, a print job submitted by a user, wherein the print job includes a large-size object. The large-size object present in the print job is processed by the printing device to ascertain the number and sizes of sheets required for printing the large-size object. Then, the large-size object is printed by the printing device on multiple sheets based on the ascertainment.
    Type: Application
    Filed: October 26, 2018
    Publication date: April 30, 2020
    Inventors: Amit Saurav, NAGARAJAN NARASIMHAN, Sivaprakash Ramasethu
  • Publication number: 20200134406
    Abstract: A printer system includes an information processing device; a printer; and a display apparatus, the information processing device being configured to control the printer and the display apparatus. A topology of the information processing device and the display apparatus includes a first topology in which the display apparatus is directly connected to the information processing device and a second topology in which the display apparatus is connected to the information processing device via the printer. The information processing device includes a processor configured to transmit to the display apparatus instruction data for the display apparatus without adding header information to the instruction data in the first topology; and transmit to the printer instruction data for the display apparatus by adding header information to the instruction data in the second topology.
    Type: Application
    Filed: October 16, 2019
    Publication date: April 30, 2020
    Inventors: Daisuke Yoshida, Yoshio Kitamura, Tomoki Ogura, Yuichi Yoshigi
  • Publication number: 20200134407
    Abstract: An image forming apparatus on which a replaceable container storing a recording material is mounted includes an image forming unit configured to form an image using the recording material, a determination unit configured to determine whether the container satisfies a predetermined condition, an acquisition unit configured to acquire an amount of the recording material used for image formation in a predetermined period and stored in the container determined as a container that satisfies the predetermined condition, a memory configured to accumulate information indicating the amount of the recording material acquired by the acquisition unit, and a prediction unit configured to predict a number of days about replacement of the container, based on the information indicating the amount of the recording material and accumulated in the memory.
    Type: Application
    Filed: October 28, 2019
    Publication date: April 30, 2020
    Inventor: Kazutaka Shinagawa
  • Publication number: 20200134408
    Abstract: Systems and methods of using ultrasonic welding to form labels with RFID tags are disclosed. The methods can be useful for the production of a large volume of labels such as production with roll-to-roll processing. The labels can be useful for consumer products such as garments.
    Type: Application
    Filed: October 30, 2019
    Publication date: April 30, 2020
    Inventor: Yuk Yu Law
  • Publication number: 20200134409
    Abstract: A tamper-proof barcoded quality indicator operative to provide a machine-readable indication of exceedance of time and temperature thresholds following actuation thereof, including a first barcode including a first colorable area and being machine-readable before exceedance of the time and temperature thresholds, a second barcode including a second colorable area and not being machine-readable before exceedance of the time and temperature thresholds, a coloring agent located at a first location on the indicator, a coloring agent pathway operative to allow the coloring agent to move, at a rate which is at least partially a function of time, from the first location to the first and second colorable areas simultaneously for simultaneous coloring thereof upon exceedance of the time and temperature thresholds, thereby causing the first barcode to become unreadable and at the same time causing the second barcode to become machine-readable, and a tamper-proof actuator element operative to actuate the indicator.
    Type: Application
    Filed: October 29, 2019
    Publication date: April 30, 2020
    Inventor: Yaron Nemet
  • Publication number: 20200134410
    Abstract: A tamper sensing element is provided which can be applied to a product having a housing or casing with a critical area where the housing or casing can be opened or separated at or along a critical area. The tamper sensing element is operable to determine if the housing or casing has been opened or separated at or along the critical area. The tamper sensing element comprises a sensor for detecting a change in a monitored parameter indicative of the housing or casing having been opened or separated at or along the critical area, a memory for storing product data and tag data; a circuit for updating the memory upon detection of a change in the parameter monitored by the sensor; and means for transmitting information contained in the memory upon being queried by a scanning device.
    Type: Application
    Filed: July 5, 2018
    Publication date: April 30, 2020
    Inventors: Michal Carrie MORGAN-ROTTMAN, Anne Marie PELLERIN
  • Publication number: 20200134411
    Abstract: A transaction card may power on the transaction card using electric current induced from an interaction of the transaction card with an electromagnetic field. The transaction card may establish a communication with a device. The communication may indicate that the transaction card has powered. The transaction card may receive, from the device, a set of instructions to configure a set of applets on the transaction card after notifying the device that the transaction card has powered on. The set of applets to be configured may be related to completing one or more different transactions. The set of applets to be configured may be different than another set of applets already configured on the transaction card. The transaction card may configure the set of applets on the transaction card according to the set of instructions after receiving the set of instructions.
    Type: Application
    Filed: December 30, 2019
    Publication date: April 30, 2020
    Inventors: Adam Koeppel, James Zarakas, Molly Johnson, Tyler Locke
  • Publication number: 20200134412
    Abstract: A wireless communication device is disclosed. The wireless communication device has a near field communications transmitter system. The device has an outer chassis that can be sized, dimensioned and decorated to resemble common household items that lack any apparent value. The wireless communication device can also include an indicia that is invisible to an unaided human eye.
    Type: Application
    Filed: March 29, 2019
    Publication date: April 30, 2020
    Inventor: Ruthie D. Lyle
  • Publication number: 20200134413
    Abstract: Embodiments of the invention relate to processes for fabricating a smart device, e.g. smart card, and configurations for smart card devices with greater reliability and lifespan, and improved finish. In the smart card device comprising of laminated substrate layers interposing a flexible film having conductor pattern thereon, at least one flip chip for operating the smart card device is embedded in a first substrate such that the first substrate provides an encapsulation to the at least one flip chip, wherein the at least one flip chip is arranged at a position in a first vertical plane; and a contact pad, for providing electrical connection when the smart card device is inserted into a smart card reader, is arranged at a position in a second vertical plane, wherein the first vertical plane is non-overlapping with the second vertical plane.
    Type: Application
    Filed: December 27, 2019
    Publication date: April 30, 2020
    Inventors: Eng Seng Ng, Sze Yong Pang
  • Publication number: 20200134414
    Abstract: According to one or more embodiments of the present invention, a computer-implemented method includes generating, by a cognitive system, an answer for a user-provided query using an analytics algorithm. The answer is based on a set of data sources. The method further includes determining an influence weightage of each data source from the set of data sources. The method further includes generating and presenting a rationale for the answer based on the influence weightage.
    Type: Application
    Filed: October 29, 2018
    Publication date: April 30, 2020
    Inventors: Yuk L. Chan, Mikhail Flom, Albert S. Jumba, Niraj Kumar, Tejinder Luthra, Sue Mallepalle, Florin-Traian Pistoleanu, Goduwin R. Ravindranath, Rekha M. Sreedharan, Abraham Sweiss, Sheryl Taylor, Hemanth Yarlagadda
  • Publication number: 20200134415
    Abstract: In accordance to embodiments, an encoder neural network is configured to receive a one-hot representation of a real text and output a latent representation of the real text generated from the one-hot representation of the real text. A decoder neural network is configured to receive the latent representation of the real text, and output a reconstructed softmax representation of the real text from the latent representation of the real text, the reconstructed softmax representation of the real text is a soft-text. A generator neural network is configured to generate artificial text based on random noise data. A discriminator neural network is configured to receive the soft-text and receive a softmax representation of the artificial text, and output a probability indicating whether the softmax representation of the artificial text received by the discriminator neural network is not from the generator neural network.
    Type: Application
    Filed: October 30, 2018
    Publication date: April 30, 2020
    Inventors: Md Akmal Haidar, Mehdi Rezagholizadeh
  • Publication number: 20200134416
    Abstract: A circuit system and a method of analyzing audio or video input data that is capable of detecting, classifying, and post-processing patterns in an input data stream. The circuit system may consist of one or more digital processors, one or more configurable spiking neural network circuits, and digital logic for the selection of two-dimensional input data. The system may use the neural network circuits for detecting and classifying patterns and one or more the digital processors to perform further detailed analyses on the input data and for signaling the result of an analysis to outputs of the system.
    Type: Application
    Filed: October 3, 2019
    Publication date: April 30, 2020
    Applicant: Electronic Warfare Associates, Inc.
    Inventors: Dirk Niggemeyer, Lester A. Foster, Elizabeth M. Rudnick
  • Publication number: 20200134417
    Abstract: Example apparatus disclosed herein include an array of processor elements, the array including rows each having a first number of processor elements and columns each having a second number of processor elements. Disclosed example apparatus also include configuration registers to store descriptors to configure the array to implement a layer of a convolutional neural network based on a dataflow schedule corresponding to one of multiple tensor processing templates, ones of the processor elements to be configured based on the descriptors to implement the one of the tensor processing templates to operate on input activation data and filter data associated with the layer of the convolutional neural network to produce output activation data associated with the layer of the convolutional neural network. Disclosed example apparatus further include memory to store the input activation data, the filter data and the output activation data associated with the layer of the convolutional neural network.
    Type: Application
    Filed: December 24, 2019
    Publication date: April 30, 2020
    Inventors: Debabrata Mohapatra, Arnab Raha, Gautham Chinya, Huichu Liu, Cormac Brick, Lance Hacking