Abstract: Disclosed is a method for cross-authenticating non-credentialed devices and trusted blockchain enabled applications using multiple communications modalities and gathering information upon request for a blockchain network.

Abstract: A method for MR imaging includes acquiring with an MR imaging apparatus undersampled k-space imaging data having one or more temporal dimensions and two or more spatial dimensions; transforming the undersampled k-space imaging data to image space data using zero-filled or sliding window reconstruction and sensitivity maps; decomposing the image space data into a compressed representation comprising a product of spatial and temporal parts, where the spatial part comprises spatial basis functions and the temporal part comprises temporal basis functions; processing the spatial basis functions and temporal basis functions to produce reconstructed spatial basis functions and reconstructed temporal basis functions, wherein the processing iteratively applies conjugate gradient and convolutional neural network updates using 2D or 3D spatial and 1D temporal networks; and decompressing the reconstructed spatial basis functions and reconstructed temporal basis functions to produce a reconstructed MRI image having one or

Abstract: The invention is a computer implemented process directed towards a Deep learning neural network architecture to create object detection model using high resolution images. More specifically, the invention is directed towards enhancing the classification accuracy and reliability of edge inspection in contact lenses. The invention is a Computer implemented process to represent a software architecture comprising software components and their inter dependencies that represents the core functional modules of an application.

Abstract: Systems and methods for identifying sequence information from measurements made on single nucleic acid molecules are disclosed. The systems and methods can include binding portions of nucleic acid molecules with marker molecules, such as fluorescent molecules and/or intercalating molecules. The marker molecules provide a detectable signal that includes information about the underlying genomic information of the location on the nucleic acid molecule where a given marker molecule is bound. A profile of the detectable signal along a position of the nucleic acid is acquired for multiple different nucleic acid molecules. The PRIMR algorithm processes the data to provide a consensus profile from which a consensus underlying genomic information can be determined.

Abstract: Methods for dehazing a digital image and for restoring an underwater digital image. The methods include the following steps: First, clustering pixels of a digital image into haze-lines, wherein each of the haze-lines is comprised of a sub-group of the pixels that are scattered non-locally over the digital image. Second, estimating, based on the haze-lines, a transmission map of the digital image, wherein the transmission map encodes scene depth information for each pixel of the digital image. Then, for a hazy image, calculating a dehazed digital image based on the transmission map.

Abstract: In some examples, an autonomous robotic welding system comprises a workspace including a part having a seam, a sensor configured to capture multiple images within the workspace, a robot configured to lay weld along the seam, and a controller. The controller is configured to identify the seam on the part in the workspace based on the multiple images, plan a path for the robot to follow when welding the seam, the path including multiple different configurations of the robot, and instruct the robot to weld the seam according to the planned path.

Abstract: The present disclosure, in some embodiments, relates to a non-transitory computer-readable medium storing computer-executable instructions. The computer readable medium is configured to cause a processor to access an image volume of a rectum comprising a rectal tumor. A forward mapping is generated based on non-rigidly registering a healthy rectal atlas to the image volume. The forward mapping is inverted to generate an inverse mapping from the image volume to the healthy rectal atlas. Based on the inverse mapping, a plurality of deformation vectors, associated with a deformation within a rectal wall of the rectum, are determined. Magnitude based deformation features and orientation based deformation features are computed from the plurality of deformation vectors. One or more of the magnitude based deformation features and one or more of the orientation based deformation features are utilized to determine a response of a patient to a chemoradiation treatment.

Abstract: A method and system for image processing is provided. The method for image processing may include: obtaining an image data set, wherein the image data set includes a first set of volume data; and determining, by the at least one processor, a target anatomy of interest based on the first set of volume data. The determining of the target anatomy of interest may include: determining an initial anatomy of interest in the first set of volume data; and editing the initial anatomy of interest to obtain the target anatomy of interest. The target anatomy of interest may include at least one region of interest (ROI) or at least one volume of interest (VOI). The initial anatomy of interest may include at least one ROI or at least one VOI.

Abstract: A method for determining the authenticity of an identity document is provided that includes capturing, by an electronic device, image data of an identity document, determining a class of the identity document, and extracting, using multi-resolution convolution and octave convolution techniques, first and second frequency components from the captured image data. The first and second frequency components correspond to different spatial frequency ranges. Moreover, the method includes determining whether the first and second frequency components satisfy matching criteria with data in corresponding frequency maps. The frequency maps are created from verified documents belonging to the determined class of document. In response to determining at least one of the first and second frequency components satisfies the matching criteria, determining the identity document is genuine.

Abstract: A data processing system receives a plurality of electronic documents in image format, and extracts text data using an optical character recognition processor. The system determines a plurality of candidate entity data and candidate context data based on the extracted text data using a trained natural language processing closed-domain question answering model. The system accesses n-gram words stored in a knowledge base, and determines similarity scores between each candidate context data and each of the n-gram words. The system determines a weighted average of the similarity scores, and selects an optimum entity data from the plurality of candidate entity data based on the weighted average of the similarity scores.

Abstract: Embodiments of the present invention provide a method for recognizing an object in a photo and determining a terminal associated with the object in the photo. The method includes: determining an object in a photo by using a biological feature recognition technology; and determining a terminal that belongs to the object in the photo based on object-terminal relationship information, so that a an apparatus such as a smart device automatically obtains information about the terminal that belongs to the object in the photo, and shares the photo with the terminal.

Abstract: The present solution can segment tracts by performing two-pass tractography. The system can first perform deterministic tractography and then probabilistic tractography. The system can use the result from the deterministic tractography to update and refine initial identified regions of interest. The refined regions of interest can be used to filter and select streamlines identified through the probabilistic tractography.

Abstract: Certain aspects of the present disclosure provide techniques for training and using machine learning models to extract key-value sets from a document. An example method generally includes identifying regions of a document including key-value sets corresponding to inputs to a data processing application based on a first machine learning model and an electronic version of the document. One or more keys and one or more values are identified in the document based on a second machine learning model. One or more key-value sets are generated based on matching keys of the one or more keys and values of the one or more values in the region of the document. The one or more key-value sets are provided to a data processing application for processing.

Abstract: Disclosed is a method for classifying hyperspectral images on the basis of an adaptive multi-scale feature extraction model, the method comprising: establishing a framework comprising the two parts of a scale reference network and a feature extraction network, introducing a condition gate mechanism into the scale reference network, performing determination step-by-step by means of three groups of modules, inputting features into a corresponding scale extraction network, deep mining rich information contained in a hyperspectral remote sensing image, effectively combining features of different scales, improving a classification effect, and generating a fine classification result map.

Abstract: A license plate detection and recognition system receives training data comprising images of license plates. The system prepares ground truth data from the training data based predefined parameters. The system trains a first machine learning algorithm based on the ground truth data to generate a license plate detection model. The license plate detection model is configured to detect one or more regions in the images. The one or more regions contains a candidate for a license plate. The LPDR system generates a bounding box for each region. The LPDR system trains a second machine learning algorithm based on the ground truth data and the license plate detection model to generate a license plate recognition model. The license plate recognition model generates a sequence of alphanumeric characters with a level of recognition confidence for the sequence.

Abstract: A method of supporting an aircraft approaching a runway is provided. Example implementations involve receiving a sequence of images, captured by a camera onboard the aircraft. Example implementations involve applying a received image to a machine learning model trained to detect the runway or a runway marking in the image, and to produce a mask that includes a segment of pixels of the image assigned to an object class for the runway or marking. Example implementations may also involve applying the mask to a corner detector to detect interest points on the mask and match the interest points to corresponding points on the runway or the marking that have known runway-framed local coordinates. Example implementations may also involve performing a perspective-n-point estimation to determine a current pose estimate of the aircraft relative to the runway or the marking and outputting the current pose estimate for use during final approach.

Abstract: Systems and methods for assessing performance of a player or a team comprising a plurality of players are described. An example method includes receiving a pass distribution matrix corresponding to a number of completed passes within a field of play for one or more players of the plurality of players, selecting a particular player from the one or more players, and generating a spine for the team. In an example, generating the spine for the team includes producing a visual representation of the field of play that illustrates a position of the particular player and at least one other player within the field of play, and automatically varying, on the visual representation, a thickness of each of a plurality of connecting lines between the particular player and the at least one other player based on the number of completed passes for the particular player.

Abstract: A method performed by an apparatus is described. The method includes receiving map data that is based on first image data, second image data, and a similarity metric. The first image data can be received from a first vehicle and represent an object. The second image data can be received from a second vehicle and represent the object. The similarity metric can be associated with the object represented in the first image data and the object represented in the second image data. The method can also include storing, by a vehicle, the received map data and localizing the vehicle based on the stored map data.

Abstract: A metadata extraction machine accesses an image that depicts an item. The item depicted in the image may have an attribute that describes a characteristic of the item and an attribute descriptor that corresponds to the attribute of the item and specifies a value of the attribute. The metadata extraction machine performs an analysis of the image. The analysis may include identifying the attribute descriptor corresponding to the attribute based on image segmentation of the image. The metadata extraction machine transmits a communication to a device of a user based on the identifying of the attribute descriptor corresponding to the attribute of the item depicted in the image.

Abstract: A compact neural network system can generate multiple individual filters from a compound filter. Each convolutional layer of a convolutional neural network can include a compound filters used to generate individual filters for that layer. The individual filters overlap in the compound filter and can be extracted using a sampling operation. The extracted individual filters can share weights with nearby filters thereby reducing the overall size of the convolutional neural network.