Abstract: The technology implements diversity sampling for a technology-assisted review of documents. An apparatus obtains an unlabeled set of documents and constructs a first batch of documents. The apparatus obtains labels for the documents and constructs a classification model using the labeled documents. The apparatus logs a found rate of a subsequent batch of documents from the unlabeled set of documents, the subsequent batch of documents being selected based on a comparison to the classification model. The apparatus determines that the classification model requires further training based on the found rate of the subsequent batch of documents and constructs a second batch of documents that includes an amount of diversity, which may be based on the found rate. The apparatus obtains labels for the second batch of documents and updates the model using the labeled second batch of documents. The method may be repeated to continue to refine the classification model.

Abstract: A system and method for synchronizing two-dimensional (“2D”) camera data for object recognition. An object recognition kiosk includes a plurality of 2D cameras and a stage for placement of one or more items. The plurality of 2D cameras capture images of items on the stage from multiple angles. The images received from the 2D cameras are concatenated into a single image. The concatenated image is processed by a trained machine learning model that analyzes and detects items present in each of the camera images that make up the concatenated image and generates 2D bounding boxes around each item. Once items are detected in the concatenated image, sensor fusion is performed based on the detected items and the bounding boxes to synchronize the image data from each of the cameras. The sensor fusion process enables the system to accurately identify the one or more items that are present on the stage.

Abstract: A system and method for synchronizing two-dimensional (“2D”) camera data for object recognition. An object recognition kiosk includes a plurality of 2D cameras and a stage for placement of one or more items. The plurality of 2D cameras, one of which acts as a reference camera, capture images of items on the stage from multiple angles. The system synchronizes image data from each camera in order to accurately identify items present on the stage. In situations where items in camera images fail to be linked to items identified in the reference camera perspective, the system maintains a fallback hierarchy of camera pairs to utilize to link items found in different camera images. The use of different camera pairs to link item detections continues down the fallback hierarchy until either all the item detections are linked or the last camera pair in the fallback hierarchy is reached.

Abstract: The present disclosure relates to the electronic document review field and, more particularly, to various apparatuses and methods of implementing batch-mode active learning for technology-assisted review (TAR) of documents (e.g., legal documents).

Abstract: The present disclosure relates to the electronic document review field and, more particularly, to various apparatuses and methods of implementing batch-mode active learning for technology-assisted review (TAR) of documents (e.g., legal documents).

Abstract: The technology implements diversity sampling for a technology-assisted review of documents. An apparatus obtains an unlabeled set of documents and constructs a first batch of documents. The apparatus obtains labels for the documents and constructs a classification model using the labeled documents. The apparatus logs a found rate of a subsequent batch of documents from the unlabeled set of documents, the subsequent batch of documents being selected based on a comparison to the classification model. The apparatus determines that the classification model requires further training based on the found rate of the subsequent batch of documents and constructs a second batch of documents that includes an amount of diversity, which may be based on the found rate. The apparatus obtains labels for the second batch of documents and updates the model using the labeled second batch of documents. The method may be repeated to continue to refine the classification model.

Abstract: The present disclosure relates to the electronic document review field and, more particularly, to various apparatuses and methods of implementing batch-mode active learning for technology-assisted review (TAR) of documents (e.g., legal documents).

Abstract: A navigation system includes: generating a rear facing camera image representing a field of view of the rear facing camera including a current roadway on which the user vehicle is traveling; generating a distortion adjustment rear facing image based on the rear facing camera image; identifying lane pixels based on correlation of image pixels of the distortion adjustment rear facing image to lane markings of the current roadway; generating a road lane model including a lane delineation estimation based on the lane pixels; and calculating a lane position for the user vehicle according to the lane delineation estimation.

Abstract: A method of operation of a navigation system includes: receiving a navigation external data including a vendor data, a delta data, or a combination thereof; generating a normalization data with a control unit based on transforming the navigation external data according to universal format; generating an aggregation changeset data by splitting the normalization data into each instance of a dimension type; and updating a navigation local data by applying the aggregation changeset data according to a layer prioritization for presenting the navigation local data on a device.

Abstract: The present disclosure relates to the electronic document review field and, more particularly, to various apparatuses and methods of implementing batch-mode active learning for technology-assisted review (TAR) of documents (e.g., legal documents).

Abstract: The present disclosure relates to the electronic document review field and, more particularly, to various apparatuses and methods of implementing batch-mode active learning for technology-assisted review (TAR) of documents (e.g., legal documents).

Abstract: The present disclosure relates to the electronic document review field and, more particularly, to various apparatuses and methods of implementing batch-mode active learning for technology-assisted review (TAR) of documents (e.g., legal documents).

Abstract: The present disclosure relates to the electronic document review field and, more particularly, to various apparatuses and methods of implementing batch-mode active learning for technology-assisted review (TAR) of documents (e.g., legal documents).

Abstract: A method of operation of a navigation system includes: detecting a source application for registering the source application to a target device; generating a first application portion for partitioning the source application for running the first application portion; and operating the first application portion for interacting with the source application for partially controlling an execution of the source application.

Abstract: A method of operation of a navigation system includes: receiving a navigation external data including a vendor data, a delta data, or a combination thereof; generating a normalization data with a control unit based on transforming the navigation external data according to universal format; generating an aggregation changeset data by splitting the normalization data into each instance of a dimension type; and updating a navigation local data by applying the aggregation changeset data according to a layer prioritization for presenting the navigation local data on a device.

Abstract: A method of operation of a navigation system includes: determining a device capability for an embedded device; receiving unprocessed map information based on the device capability; generating a natively rendered map layer on a mobile device with the unprocessed map information; generating a map overlay for layering over the natively rendered map layer; and generating a navigation interface with the map overlay and the natively rendered map layer for displaying on the embedded device.

Abstract: A method of operation of a navigation system includes: receiving an entry for a destination, a sub-destination, or a combination thereof with the sub-destination located within the destination; receiving a road obstacle image while traveling along a route to reach the destination; generating an operation direction based on the road obstacle image; and generating a destination image representing the destination for displaying on a device.

Abstract: A method of operation of a navigation system includes: generating a potential route based on a navigation information, a status information, or a combination thereof; determining an update priority based on comparing a first map and the potential route on a second map with a control unit for identifying a discrepancy between the first map and the second map; and updating the first map based on the update priority for displaying on a device.

Abstract: The present disclosure relates to the electronic document review field and, more particularly, to various apparatuses and methods of implementing batch-mode active learning for technology-assisted review (TAR) of documents (e.g., legal documents).

Abstract: The present disclosure relates to the electronic document review field and, more particularly, to various apparatuses and methods of implementing batch-mode active learning for technology-assisted review (TAR) of documents (e.g., legal documents).