Abstract: A method comprises receiving a set of model points of a model of one or more passageways of a patient. The method further comprises receiving a set of measured points collected from within the one or more passageways of the patient. Each point comprises coordinates within a medical environment occupied by the patient. The method further comprises matching each measured point to a model point to generate a set of matches. The method further comprises assigning a weight to each of the measured points based on the set of matches to generate a weighted set of matches. The method further comprises moving the set of measured points relative to the set of model points based on the weighted set of matches.

Abstract: A method for 3D object perception is described. The method includes extracting features from each image of a synthetic stereo pair of images. The method also includes generating a low-resolution disparity image based on the features extracted from each image of the synthetic stereo pair images. The method further includes predicting, by a trained neural network, a feature map based on the low-resolution disparity image and one of the synthetic stereo pair of images. The method also includes generating, by a perception prediction head, a perception prediction of a detected 3D object based on the feature map predicted by the trained neural network.

Abstract: Provided are an apparatus and method for recognizing whether an action objective is achieved. The apparatus includes a video feature extraction module configured to receive a video and output a video feature sequence through an operator, such as a convolution operator, an action case memory module configured to compress and store action case information for each action type and each of success and failure groups transmitted from the video feature extraction module and return the action case information according to a query including a pair of an action type and whether the action is successful, and an action success or failure determination module configured to receive a pair of a video feature sequence and an action type identifier and output whether an action of the given video feature sequence is successful in connection with the action case memory module.

Abstract: A multi-task text infilling system receives a digital image and identifies a region of interest of the image that contains original text. The system uses a machine learning model to determine, in parallel: a foreground image that includes the original text; a background image that omits the original text; and a binary mask that distinguishes foreground pixels from background pixels, The system receives a target mask that contains replacement text. The system then applies the target mask to blend the background image with the foreground layer image and yield a modified digital image that includes the replacement text and omits the original text.

Abstract: Implementations are described herein for training a remote sensing machine learning model. In various implementations, ground-truth low elevation images that depict particular crop(s) in particular agricultural area(s) and terrain conditions observed in the agricultural area(s) are identified. A plurality of low elevation training images is generated based on the ground truth low elevation training images to include the plurality of ground truth low elevation images and synthetic low elevation images generated based on synthetic terrain conditions. The plurality of low-elevation training images are processed using a synthetic satellite image machine learning model to generate the plurality of synthetic satellite training images, which are then processed by the remote sensing machine learning model to generate inferred terrain conditions.

Abstract: A method for detecting the presence and the correct or incorrect placement of target objects in a container or carrier divides the container space into areas where the states of placement of the target objects in the container can be recognized, to generate N number of sub-areas, N is a positive integer. An artificial intelligence model is obtained by training the same according to training images of objects, the training images being images of the N sub-areas. The images are input into the artificial intelligence model and the states of placement are determined. The disclosure also provides an electronic device and a non-transitory storage medium.

Abstract: An inspection apparatus includes processing circuitry. The processing circuitry acquires read image data obtained by reading an image printed on both sides of a conveyance medium. The processing circuitry searches for marks printed on both sides of the conveyance medium in the read image data. The processing circuitry outputs information indicating a misalignment amount of both sides of the conveyance medium based on positions where the marks are printed.

Abstract: Provided in the present invention are a magnetic resonance imaging system and method, and a computer-readable storage medium. The method comprises: performing a medical scan of a subject and acquiring a first medical image having a first noise interference artifact, and performing an additional scan of the subject to acquire a second medical image, wherein the second medical image has a second noise interference artifact, and the location mapping of the second noise interference artifact in the first medical image is symmetrical to the location of the first noise interference artifact relative to a pixel center of the first medical image; and performing synthesis-related processing on the first medical image and the second medical image to acquire a post-processed image with reduced noise interference artifacts.

Abstract: The present disclosure may provide a method for movement control. The method may include obtaining at least one tracking parameter associated with a moving object and a control algorithm including a first control algorithm and a second control algorithm associated with a capture device used to track the moving object. The method may also include determining a switching time point with respect to the first control algorithm and the second control algorithm. Further, the method may include accelerating, according to the first control algorithm, a speed of the capture device within a first acceleration time period from a start time point to the switching time point and accelerating, according to the second control algorithm from the switching time point to an acceleration termination time point.

Abstract: An image processing system includes circuitry that generates up-sampled images corresponding to input images based on the input images, image realism prediction values, and a corresponding semantic feature mask. The circuitry generates the image realism prediction values based on at least one of the input images and the up-sampled images, and generates the semantic feature mask based on at least one of the input images and the up-sampled images.

Abstract: An automobile vehicle visual wireless-based positioning system, incudes an automobile vehicle having a radio receiver. A map contains candidate locations of access-points (APs) and access-point corresponding media-access-control (MAC) IDs. A wireless range sensor determines different ranges of various detected APs visible to the automobile vehicle. An image collection feature identifies image data visible to the automobile vehicle. A real-time feature matching element matching features identified by image collection feature with data from the map. A filter receives an output from the real-time feature matching element to generate an automobile vehicle pose.

Abstract: A map building apparatus includes a memory storing instructions, and a processor executing the instructions to obtain a plurality of frames of images that carry image information of a target environment, obtain a motion parameter of the image capture component at a capture location of each frame of the plurality of frames of images, obtain a relative displacement between capture locations of each two frames of images based on the motion parameter of the image capture component, obtain, based on the plurality of frames of images and the relative displacement, a map layer including feature points in the plurality of frames of images, and send the map layer and the relative displacement to a server. The plurality of frames of images are captured by an image capture component. The motion parameter indicates a motion status of the image capture component. The map layer is useable to build a map.

Abstract: Modules for housing electronic and electromechanical medical equipment including a system to measure and record administration of one or more IV medications or fluids for IV administration.

Abstract: A method for performing a welding procedure includes determining conditions of the welding procedure using a virtual image of a structure on which the welding procedure is to be performed. The method further includes generating specifications for performing the welding procedure based on the conditions. The method further includes generating a virtual reference shape based on the conditions and the specifications, the virtual reference shape generated by modifying the virtual image. The method further includes comparing a resulting shape of the welding procedure with the virtual reference shape. The method further includes determining a quality of the welding procedure based on the comparison. The method further includes storing data pertaining to the welding procedure.

Abstract: A system includes a plurality of satellites orbiting around a celestial body in a plurality of orbital planes. Each satellite includes an imaging device having a field of view (FOV) to capture an image of a sky that includes celestial image features of resident space object (RSO), stars, and/or planets. The satellite processor is configured to input the image data for each image into a pre-processing software pipeline to generate for each image a contrast-enhanced image data replica of each image, and an enhanced image data replica of each image, to receive from an output of a known-unknown RSO split data processing pipeline, a determination that a candidate RSO is a known RSO stored in an RSO catalog, or an unknown RSO, and to assign to the candidate RSO based on the determination, an RSO ID of the known RSO listed in the RSO catalog, or a new RSO ID.

Abstract: The present disclosure describes approaches for evaluating interest points for localization uses based on a repeatability of the detection of the interest point in images capturing a scene that includes the interest point. The repeatability of interest points is determined by using a trained repeatability model. The repeatability model is trained by analyzing a time series of images of a scene and determining repeatability functions for each interest point in the scene. The repeatability function is determined by identifying which images in the time series of images allowed for the detection of the interest point by an interest point detection model.

Abstract: A verification apparatus reads an image of a printed sheet using a plurality of imaging units to obtain image data. The verification apparatus extracts feature points of the obtained image data and determines whether a feature point of first image data obtained by a first imaging unit should be a feature point of second image data that should be obtained by another imaging unit. If so, the verification apparatus converts coordinates of the feature point of the second image data to a coordinate system of the first imaging unit, calculates a geometrical conversion parameter from the coordinates of the converted feature point and coordinates of feature points other than the converted feature point, and aligns the image data of the printed sheet and a correct image based on the geometrical conversion parameter.

Abstract: A control unit of a processing apparatus detects a linear region corresponding to a first planned dividing line from an intersection region of the first planned dividing line and a second planned dividing line, obtains an angle between the linear region and an X-axis direction, and positions the linear region corresponding to the first planned dividing line in the X-axis direction. A linear region corresponding to a next first planned dividing line is detected and an interval between the first planned dividing lines is set. A second planned dividing line interval setting section detects two linear regions corresponding to second planned dividing lines, the linear regions being adjacent to each other, and an interval is set between the second planned dividing lines. A device image enclosed by a pair of first planned dividing lines and a pair of second planned dividing lines is generated and stored.

Abstract: Systems and methods are described herein for tracking an elongate instrument or other medical instrument in an image.

Abstract: Systems and methods are disclosed for receiving a target image corresponding to a target specimen, the target specimen comprising a tissue sample of a patient, applying a machine learning model to the target image to determine at least one characteristic of the target specimen and/or at least one characteristic of the target image, the machine learning model having been generated by processing a plurality of training images to predict at least one characteristic, the training images comprising images of human tissue and/or images that are algorithmically generated, and outputting the at least one characteristic of the target specimen and/or the at least one characteristic of the target image.