Patents Examined by Michael Adam Shariff
  • Patent number: 11990224
    Abstract: Methods, devices, and systems that are related to facilitating an automated, fast and accurate model for cardiac image segmentation, particularly for image data of children with complex congenital heart disease are disclosed. In one example aspect, a generative adversarial network is disclosed. The generative adversarial network includes a generator configured to generate synthetic imaging samples associated with a cardiovascular system, and a discriminator configured to receive the synthetic imaging samples from the generator and determine probabilities indicating likelihood of the synthetic imaging samples corresponding to real cardiovascular imaging sample. The discriminator is further configured to provide the probabilities determined by the discriminator to the generator and the discriminator to allow the parameters of the generator and the parameters of the discriminator to be adjusted iteratively until an equilibrium between the generator and the discriminator is established.
    Type: Grant
    Filed: March 26, 2021
    Date of Patent: May 21, 2024
    Assignee: THE REGENTS OF THE UNIVERSITY OF CALIFORNIA
    Inventors: Hamid Jafarkhani, Saeed Karimi-Bidhendi, Arash Kheradvar
  • Patent number: 11983849
    Abstract: An image filling method and apparatus, a device and a storage medium are disclosed. The image filling method includes: performing multilevel encoding processing on features of an image to be filled to generate multilevel encoded feature layers, sizes of the multilevel encoded feature layers being reduced layer by layer; performing layer-by-layer decoding processing on the multilevel encoded feature layers to obtain multilevel decoded feature layers and a first image, there being no missing region in the first image, wherein the layer-by-layer decoding processing includes a concatenation operation on a decoded feature layer and an encoded feature layer with a same size; and performing up-sampling processing on the first image to obtain multilevel up-sampled feature layers and a second image optimized by the up-sampling processing, the up-sampling processing including a concatenation operation on an up-sampled feature layer and a decoded feature layer with a same size.
    Type: Grant
    Filed: March 16, 2021
    Date of Patent: May 14, 2024
    Assignee: BEIJING BAIDU NETCOM SCIENCE AND TECHNOLOGY CO., LTD.
    Inventors: Chao Li, Dongliang He, Fu Li, Hao Sun
  • Patent number: 11968471
    Abstract: Embodiments relate to extracting features from images, such as by identifying keypoints and generating keypoint descriptors of the keypoints. An apparatus includes a pyramid image generator circuit, a keypoint descriptor generator circuit, and a pyramid image buffer. The pyramid image generator circuit generates an image pyramid from an input image. The keypoint descriptor generator circuit processes the pyramid images for keypoint descriptor generation. The pyramid image buffer stores different portions of the pyramid images generated by the pyramid image generator circuit at different times and provides the stored portions of the pyramid images to the keypoint descriptor generator circuit for keypoint descriptor generation. When first portions of the pyramid images are no longer needed for the keypoint descriptor generation, the first portions are removed from the pyramid image buffer to provide space for second portions of the pyramid images that are needed for the keypoint descriptor generation.
    Type: Grant
    Filed: March 8, 2021
    Date of Patent: April 23, 2024
    Assignee: APPLE INC.
    Inventors: David R. Pope, Liran Fishel, Assaf Metuki, Muge Wang
  • Patent number: 11961275
    Abstract: A computer-implemented method for training a normalizing flow. The normalizing flow predicts a first density value based on a first input image. The first density value characterizes a likelihood of the first input image to occur. The first density value is predicted based on an intermediate output of a first convolutional layer of the normalizing flow. The intermediate output is determined based on a plurality of weights of the first convolutional layer. The method for training includes: determining a second input image; determining an output, wherein the output is determined by providing the second input image to the normalizing flow and providing an output of the normalizing flow as output; determining a second density value based on the output tensor and on the plurality of weights; determining a natural gradient of the plurality of weights with respect to the second density value; adapting the weights according to the natural gradient.
    Type: Grant
    Filed: August 16, 2021
    Date of Patent: April 16, 2024
    Assignee: ROBERT BOSCH GMBH
    Inventors: Jorn Peters, Thomas Andy Keller, Anna Khoreva, Emiel Hoogeboom, Max Welling, Priyank Jaini
  • Patent number: 11948354
    Abstract: Disclosed are systems, methods, and apparatus related to automated spectral selection for feature identification from remote sensed images. The invention includes various modules, such as a spectral selection processing module and a user device module that are communicatively coupled to each other via a communication connection. The invention includes a non-transitory memory that causes a processor to carry out one or more tasks. Those tasks include, but are not limited to, storing imagery; generating a list of imagery, input related to the imagery, a map view, target pixel values, and geometry related to the imagery; transforming pixels to vectors; conducting analytics within the identified vector features; quantifying data within identified vector features; and displaying the results on the user device module.
    Type: Grant
    Filed: May 28, 2021
    Date of Patent: April 2, 2024
    Assignee: Cultivate Agricultural Intelligence, LLC
    Inventors: Jill Marie Stanford, Jeff Germain, Jeremy Folds, Bob Binckes
  • Patent number: 11941879
    Abstract: Implementations are disclosed for selectively operating edge-based sensors and/or computational resources under circumstances dictated by observation of targeted plant trait(s) to generate targeted agricultural inferences. In various implementations, triage data may be acquired at a first level of detail from a sensor of an edge computing node carried through an agricultural field. The triage data may be locally processed at the edge using machine learning model(s) to detect targeted plant trait(s) exhibited by plant(s) in the field. Based on the detected plant trait(s), a region of interest (ROI) may be established in the field. Targeted inference data may be acquired at a second, greater level of detail from the sensor while the sensor is carried through the ROI. The targeted inference data may be locally processed at the edge using one or more of the machine learning models to make a targeted inference about plants within the ROI.
    Type: Grant
    Filed: October 22, 2020
    Date of Patent: March 26, 2024
    Assignee: MINERAL EARTH SCIENCES LLC
    Inventors: Sergey Yaroshenko, Zhiqiang Yuan
  • Patent number: 11941878
    Abstract: A fully-automated computer-implemented system and method for generating a road network map from a remote sensing (RS) image in which the classification accuracy is satisfactory combines moving vehicle detection with spectral classification to overcome the limitations of each. Moving vehicle detections from an RS image are used as seeds to extract and characterize image-specific spectral roadway signatures from the same RS image. The RS image is then searched and the signatures matched against the scene to grow a road network map. The entire process can be performed using the radiance measurements of the scene without having to perform the complicated geometric and atmospheric conversions, thus improving computational efficiency, the accuracy of moving vehicle detection (location, speed, heading) and ultimately classification accuracy.
    Type: Grant
    Filed: June 25, 2021
    Date of Patent: March 26, 2024
    Assignee: Raytheon Company
    Inventors: Grant B. Boroughs, John J. Coogan, Lisa A. McCoy
  • Patent number: 11915467
    Abstract: Example solutions provide saliency for anchor-based object detection, and include: performing, with an object detector, a first object detection process on an image, wherein the first object detection process employs a plurality of anchor boxes; identifying an object detection result for the image; determining, from among the plurality of anchor boxes, a first anchor box associated with the object detection result; and while limiting the object detector to the first anchor box, generating, with the object detector, a saliency map for the image. In some examples, the saliency map is used for selecting further training data for the object detector. In some examples, the saliency map comprises a gradient-based saliency map, and is used for auditing or debugging the object detector.
    Type: Grant
    Filed: August 11, 2022
    Date of Patent: February 27, 2024
    Assignee: Microsoft Technology Licensing, LLC.
    Inventor: James Brian Hall
  • Patent number: 11908149
    Abstract: Provided is a system configured to obtain a set of images via a camera of the computing device, input the set of images into a neural network, and detect a target physical object with the neural network. The system may determine a contour of the target physical object and a first three-dimensional reconstruction of the target physical object. The system may generate a virtual representation and a virtual object based on attributes of the virtual representation, where a first attribute of the set of attributes includes the first three-dimensional reconstruction. The system may associate the virtual object with the virtual representation and displays the virtual object at pixel coordinates of a display that at least partially occlude at least part of the target physical object, where a position of the virtual object is computed based on the contour.
    Type: Grant
    Filed: October 12, 2020
    Date of Patent: February 20, 2024
    Inventor: Andrew Thomas Busey
  • Patent number: 11908160
    Abstract: A method of detecting an object in an image using a convolutional neural network (CNN) includes generating, based on the image, a plurality of reference feature maps and a corresponding feature pyramid including a plurality of final feature maps; obtaining a proposed region of interest (ROI); generating at least a first context ROI having an area larger than an area of the proposed ROI; assigning the proposed ROI and the first context ROI to a first and second final feature maps having different sizes; extracting, by performing ROI pooling, a first set of features from the first final feature map using the proposed ROI and a second set of features from the second final feature map using the first context ROI; and determining, based on the first and second sets of extracted features, at least one of a location of the object and a class of the object.
    Type: Grant
    Filed: October 12, 2018
    Date of Patent: February 20, 2024
    Assignee: NOKIA TECHNOLOGIES OY
    Inventor: Jing Nie
  • Patent number: 11900686
    Abstract: Techniques for improving image processing related to item deliveries are described. In an example, a computer system receives an image showing a drop-off of an item, the item associated with a delivery to a delivery location. The computer system inputs the image to a first artificial intelligence (AI) model. The computer system receives first data comprising an indication of whether the drop-off is correct from the first AI model. The computer system causes a presentation of the indication at a device associated with the delivery of the item to the delivery location.
    Type: Grant
    Filed: November 4, 2020
    Date of Patent: February 13, 2024
    Assignee: Amazon Tecnologies, Inc.
    Inventors: Zheshen Wang, Dimitris Papadimitriou, Mehran Kafai, Jarrod Sherwin, Anthony Sharma
  • Patent number: 11900706
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for tracking objects of interest using distance-based thresholding. One of the methods includes detecting an object depicted in an image captured by a camera, determining a predicted physical distance between the object and the camera, selecting, from a plurality of predetermined confidence thresholds, a confidence threshold for the predicted physical distance, each confidence threshold in the plurality of predetermined confidence thresholds for a different physical distance range, the confidence threshold having a physical distance range that includes the predicted physical distance, and determining, using the confidence threshold and a confidence score that indicates a likelihood that the object is an object of interest, that the object is likely an object of interest.
    Type: Grant
    Filed: September 24, 2020
    Date of Patent: February 13, 2024
    Assignee: ObjectVideo Labs, LLC
    Inventors: Gang Qian, Allison Beach, Sima Taheri, Sravanthi Bondugula, Sung Chun Lee, Narayanan Ramanathan
  • Patent number: 11869230
    Abstract: A computer-implemented method of forecasting the semantic output of at least one frame, the method comprising the steps of receiving the input frames from a camera up to a predetermined time, processing via a down-sampling module of a neural network the plurality of input frames to receive a plurality of feature tensors, determining spatio-temporal correlations between the plurality of feature tensors, processing the plurality of feature tensors and the spatio-temporal correlations to receive at least one forecasted feature tensor, and processing via an up-sampling module of the neural network the at least one forecasted feature to receive at least one forecasted semantic output for a time larger than the predetermined time.
    Type: Grant
    Filed: June 4, 2021
    Date of Patent: January 9, 2024
    Assignee: RIMAC AUTOMOBILES LTD.
    Inventors: Tonci Antunovic, Marin Orsic, Josip Saric, Sinisa Segvic, Sacha Vrazic
  • Patent number: 11854259
    Abstract: Aspects of the subject technology relate to determining a holdup measurement based on a gamma spectrum through machine learning. A spectral image based on a gamma spectrum generated downhole in a wellbore can be accessed. A component of a holdup measurement for the wellbore can be classified into a specific quantized level through application of a machine learning classification model to the spectral image. A continuous value for the component of the holdup measurement for the wellbore can be quantified by applying a machine learning quantization model associated with the quantized level.
    Type: Grant
    Filed: December 30, 2021
    Date of Patent: December 26, 2023
    Assignee: HALLIBURTON ENERGY SERVICES, INC.
    Inventors: Mayir Mamtimin, Jeffrey James Crawford, Weijun Guo
  • Patent number: 11835997
    Abstract: A system for determining a location of a lighting fixture in a venue includes a camera and a controller. The camera captures images of the lighting fixture. The controller is operatively coupled to the camera. The controller designates a first position of the camera, receives a first image of the lighting fixture from the camera in the first position, determines a first distance vector between the first position and the lighting fixture based on the first image, designates a second position of the camera, receives a second image of the lighting fixture from the camera in the second position, determines a second distance vector between the second position and the lighting fixture based on the second image, determines a vector relationship location to be a location nearest both the first distance vector and the second distance vector, and designates the vector relationship location as the location of the lighting fixture.
    Type: Grant
    Filed: September 22, 2020
    Date of Patent: December 5, 2023
    Assignee: Electronic Theatre Controls, Inc.
    Inventors: Matt Halberstadt, Josh Jordan, Zoe Wolter, Dennis Varian, Lowell Olcott
  • Patent number: 11830167
    Abstract: A system and a method for super-resolution image processing in remote sensing are disclosed. One or more sets of multi-temporal images with an input resolution and one or more first target images with a first output resolution are generated from one or more data sources. The first output resolution is higher than the input resolution. Each set of multi-temporal images is processed to improve an image match in the corresponding set of multi-temporal images. The one or more sets of multi-temporal images are associated with the one or more first target images to generate a training dataset. A deep learning model is trained using the training dataset. The deep learning model is provided for subsequent super-resolution image processing.
    Type: Grant
    Filed: June 21, 2021
    Date of Patent: November 28, 2023
    Inventors: Yuchuan Gou, Juihsin Lai, Mei Han
  • Patent number: 11823045
    Abstract: An encoding apparatus is provided. The apparatus comprises an input unit operable to obtain a plurality of training images, said training images being for use in training a machine learning model. The apparatus also comprises a label unit operable to obtain a class label associated with the training images; and a key unit operable to obtain a secret key for use in encoding the training images. The apparatus further comprises an image noise generator operable to generate, based on the obtained secret key, noise for introducing into the training images. The image noise generator is configured to generate noise that correlates with the class label associated with the training images such that a machine learning model subsequently trained with the modified training images learns to associate the introduced noise with the class label for those images. A corresponding decoding apparatus is also provided.
    Type: Grant
    Filed: October 20, 2020
    Date of Patent: November 21, 2023
    Assignee: Sony Interactive Entertainment Inc.
    Inventors: Mark Jacobus Breugelmans, Oliver Hume, Fabio Cappello, Nigel John Williams
  • Patent number: 11810333
    Abstract: A method and an apparatus for generating an image are provided. The method includes: acquiring a screenshot of a webpage preloaded by a terminal as a source image; recognizing connection areas in the source image, and generating first circumscribed rectangular frames outside outlines of the connection areas; combining, in response to determining that a distance between the connection areas is smaller than a preset distance threshold, the connection areas, and generating a second circumscribed rectangular frame outside outlines of the combined connection areas; and generating, based on a nested relationship between the first circumscribed rectangular frames and the second circumscribed rectangular frames and pictures in the first circumscribed rectangular frames, a target image. The first circumscribed rectangular frames and the second circumscribed rectangular frame are respectively generated by recognizing and combining the connection areas in the source image.
    Type: Grant
    Filed: March 19, 2021
    Date of Patent: November 7, 2023
    Assignee: Baidu Online Network Technology (Beijing) Co., Ltd.
    Inventors: Yang Jiao, Yi Yang, Jianguo Wang, Yi Li, Xiaodong Chen, Lin Liu, Xiang He, Yanfeng Zhu
  • Patent number: 11803941
    Abstract: A method for removing fringe noise in an image includes: acquiring an original image; acquiring an original frequency spectrum of one-dimensional signal of the original image; determining a noise frequency band in the original frequency spectrum, and the noise frequency band is a frequency band including a central frequency of the fringe noise; denoising the noise frequency band to obtain a denoised frequency spectrum, wherein a denoising intensity used in the denoising is gradually increased from a start frequency position of the noise frequency band, and the denoising intensity is gradually reduced from the central frequency until a stop frequency position of the noise frequency band; and generating a denoised image according to the denoised frequency spectrum.
    Type: Grant
    Filed: September 23, 2020
    Date of Patent: October 31, 2023
    Assignee: BOE TECHNOLOGY GROUP CO., LTD.
    Inventor: Guannan Chen
  • Patent number: 11790646
    Abstract: A method for human-object interaction detection includes receiving an image. A set of features are extracted from multiple positions of the image. One or more human-object pairs may be predicted based on the extracted set of features. A human-object interaction may be determined based on a set of candidate interactions and the predicted human-object pairs.
    Type: Grant
    Filed: June 25, 2021
    Date of Patent: October 17, 2023
    Assignee: QUALCOMM Technologies, Inc.
    Inventors: Mert Kilickaya, Arnold Wilhelmus Maria Smeulders