Abstract: The present disclosure provides for a system for facilitating a completely automated process that may directly fetch an imagery of a given location and area from any mapping module and extract a plurality of objects in the given imagery. Further, a deep learning-based object segmentation such as but not limited to a cascaded reverse mask RCNN framework method may generate a set of predefined vectors associated with the image. The system may be configured to automate the generation of the predefined vectors based on the image received from the image sensing assembly.

Abstract: An apparatus, system, method, and computer-readable medium include aspects for using surgical video analysis. The aspects utilize intracorporeal video footage, image analysis, and notifications to optimize correspondences among medical procedure information, medical guidelines, and medical transaction information.

Abstract: A labeling method and a computing device by detecting lesion region in images using a learned network function. The method includes obtaining a medical image, detecting and displaying a region of interest corresponding to at least one subject disease through a learned network function, and labeling a lesion region corresponding to the at least one subject disease on the medical image according to the region of interest and user inputs. The labeling includes receiving a first user input for choosing a selected region within the region of interest, setting a reference pixel value based on the selected region, detecting and displaying a lesion estimation region having pixel values within a predetermined range from the reference pixel value, and correcting the lesion estimation region according to a second user input to label the lesion region.

Abstract: The present disclosure discloses a method for positioning. The method may include obtaining a scout image of a target object and inputting the scout image of the target object into a positioning model. The method may also include determining a positioning frame in the scout image based on an output result of the positioning model. The positioning model may be obtained by training based on training scout images and information of the gold standard positioning frames. Each of the gold standard positioning frames may be in, from, or determined based on one of the training scout images and used for scanning.

Abstract: A stop line detection apparatus recognizes a boundary line of a lane on which the host vehicle travels, and detect a stop line at an intersection in front of the host vehicle. The apparatus sets an intersection area corresponding to the intersection in the road on which the host vehicle travels on the basis of a captured image by a front camera of the host vehicle, detects a crosswalk in the intersection area, a stop line search area setting unit configured to set a stop line search area extending from the crosswalk toward a front side in the lane on which the host vehicle travels, and performs stop line detection in the stop line search area. A depth of the stop line search area in an extending direction of a traveling lane is smaller than twice a depth of the crosswalk.

Abstract: An improved apparatus and method for extracting pattern contour information from an inspection image in a multiple charged-particle beam inspection system are disclosed. An improved method for extracting pattern contour information from an inspection image comprises identifying, from an inspection image obtained from a charged-particle beam inspection system, a first pattern and a second pattern that partially overlap in the inspection image. The method also comprises generating a first separation image by removing an image area corresponding to the second pattern from the inspection image. The first separation image includes the first pattern of which a first part is removed when removing the image area corresponding to the second pattern. The method also comprises updating the first separation image to include image data representing the removed first part of the first pattern based on a first reference image corresponding to the first pattern.

Abstract: A method, apparatus and system for prediction of a neonatal brain development prognosis, using a pregenerated brain neurodevelopment prediction model. The apparatus includes a computing device, which includes a memory; and at least one processor performing communication with the memory. The processor is configured to extract cerebral blood flow (CBF) and brain tissue relaxation times T1 and T2 from the input magnetic resonance imaging (MRI) of a subject newborn, generate brain neurodevelopment prediction data of the subject newborn using a pregenerated brain neurodevelopment prediction model, and control the output of the generated brain neurodevelopment prediction data of the subject newborn.

Abstract: A stacking inspection apparatus includes: camera units that generate an aligned image by photographing four corner points of the outer periphery of the electrode plates or the unit cells at an upper part in a stacking direction of the electrode plates or the unit cells; and light irradiation units that irradiate light signals to four corner of the inspection object, and sensors that recognize the light signal irradiated from the light irradiation units and determine whether or not alignment of the first electrode plate and the second electrode plate is defective.

Abstract: Embodiments of the present application provide a method and apparatus of determining a dispensing position, a dispensing system for batteries, an electronic device and a medium. The method of determining a dispensing position includes receiving an image of a battery module, processing the image to obtain a contour feature image of at least one object on the battery module, and determining, based on the contour feature image, a dispensing position of the at least one object.

Abstract: An image processing method according to the present disclosure includes the steps of receiving at least one piece of image data as an input, assigning a plurality of feature points to the image data, and modifying a part of the image data based on a feature line generated by connecting at least two of the plurality of feature points or a feature region generated by connecting at least three of the plurality of feature points.

Abstract: A method for determining a charge characteristic of electrical charges of particles in a fluid stream includes directing the fluid stream containing particles through a fluid line. Then a spatially-resolved determination of a measuring field-less particle velocity in a measurement area without an electrical measuring field is performed. An electrical measuring field is applied transverse to the flow direction in the measurement area. A spatially-resolved determination of a midfield particle velocity in the measurement area is determined. At least one charge characteristic which denotes an electrostatic charge of the particles is determined from the spatially-resolved particle velocities.

Abstract: Disclosed herein are methods, systems, and computer-readable media for generating and using unbinned image data, characterized by (a) receiving image data corresponding to an image; (b) generating the unbinned image data by performing an unbinning operation on the received image data, wherein the unbinning operation is characterized by conditions of invertibility and smoothness; and (c) using the unbinned image data for either: (i) displaying a version of the image based on the unbinned image data; and/or (ii) performing image processing.

Abstract: Apparatus, system, method, and computer-readable medium aspects for using surgical video analysis for improving compliance with medical guidelines and improving processing of medical bills, medical malpractice claims, and insurance claims are described. The aspects utilize intracorporeal video footage, image analysis, and notifications to optimize correspondences among medical procedure information, medical guidelines, and medical transaction information.

Abstract: A system is provided that includes a server; and a plurality of user devices, wherein processing circuitry of each of the user devices is configured to execute an application that displays an image of a person with a type of hair curl pattern; and receives an input of the respective user on the user's opinion on the type of hair curl pattern of the person in the displayed image; wherein the processing circuitry of the server is configured to receive the input of the user input from each of the plurality of user devices; and update a machine learning model for performing image analysis to determine a type of curl pattern present in an image based on the received inputs from each of the plurality of devices.

Abstract: Location operation conflict resolution techniques are described. In these techniques, a likely user's intent is inferred by a digital image editing system to prioritize anchor points that are to be a subject of a location operation. In an example in which multiple anchor points qualify for location operations at a same time, these techniques are usable to resolve conflicts between the anchor points based on an assigned priority. In an implementation, the priority is based on selection input location with respect to an object.

Abstract: An information generation method and apparatus, an electronic device, and a computer readable medium. The method comprises: generating a target region set on the basis of an obtained first target picture (201); selecting a target region satisfying a preset condition from the target region set as a candidate region to obtain a candidate region set (202); generating a second target picture on the basis of the candidate region set (203); and generating picture related information on the basis of the second target picture (204). Thus, effective extraction for a target region and further classification for the target region are achieved, so that an identification result of an image region is finer, and then the subsequent image processing technology has a promotion space.

Abstract: This invention is related to a method for determining the storage quality of an X-ray imaging plate, including the steps of: providing a plurality of digital X-ray images of the imaging plate; performing a cross-correlation operation on the X-ray images for relevant image regions; creating feature images from the correlation values; classifying the functionality of a pixel of a feature image based on the number of pixels in the vicinity of the pixel whose correlation value exceeds a correlation threshold. Further, the invention also relates to an apparatus.

Abstract: Systems and methods are provided for ultrafast light field tomography (LIFT), a transient imaging strategy that offers a temporal sequence of over 1000 and enables highly efficient light field acquisition, allowing snapshot acquisition of the complete two, three or four-dimensional space and time. The apparatus transforms targets in object space into parallel lines in the image plane with a cylindrical lens. Beam projections are optionally directed through a Dove prism and an array of cylindrical lenslets to an imaging device such as a SPAD camera, streak camera and CCD camera. By using an array of cylindrical lenslets oriented at distinct angles, enough projections are obtained simultaneously to recover the image with a single snapshot. The time-resolved system and methods were adapted to LIDAR, hyperspectral, non-line-of-sight, and three-dimensional transient imaging.

Abstract: Provided is a remote sensing image feature discretization method based on rough-fuzzy model, comprising the following steps: listing the digital number in each band and category of a selected sample in remote sensing images, and building an image information decision table based on the digital number and category; initializing the class center of each category and the membership degree of a sample example relative to the class center; updating the class center of each category and the membership degree of the sample example relative to the class center iteratively, and obtaining the final value of the class center of each category and the final value of the membership degree; building a rough-fuzzy set, computing the mean approximation accuracy of the rough-fuzzy set, discretizing the image information decision table, evaluating the discretization results based on the mean approximation accuracy and a genetic algorithm, and selecting an optimal discretization solution.

Abstract: A method comprises: first, obtaining a to-be-recognized lane line image; then determining, based on the lane line image, a candidate pixel used to recognize a lane line region, to obtain a candidate point set, where the lane line region is a region of a location of a lane line in the lane line image and a surrounding region of the location of the lane line; then selecting a target pixel from the candidate point set, and obtaining at least three location points associated with the target pixel in a neighborhood, where the at least three location points are on one lane line; and finally, performing extension by using the target pixel as a start point and based on the at least three location points associated with the target pixel, to obtain a lane line point set corresponding to the target pixel.