Abstract: An illustrative method includes accessing, by a computing device, a model simulating light scattered by a simulated target, the model comprising a plurality of parameters. The method further includes generating, by the computing device, a set of possible histogram data using the model with a plurality of values for the parameters. The method further includes determining, by the computing device, a set of components that represent the set of possible histogram data, the set of components having a reduced dimensionality from the set of possible histogram data.

Abstract: A training data generation device performs the processes of: acquiring first correct answer data that is correct answer data with respect to each training image of a training image group, the training image group including plural training images to be given the correct answer data, the training image group being divided into plural image subgroups, the first correct answer data being generated in a different situation for each of the plural image subgroups; generating a discriminator with respect to the each of the plural image subgroups, the discriminator being learned based on the each of the plural image subgroups and the first correct answer data corresponding to the each of the plural image subgroups; acquiring a discrimination result outputted by the discriminator for each of the plural training images by inputting the each of the plural training images to the discriminator which is generated based on at least one image subgroup other than an image subgroup to which the each of the training images belon

Abstract: An information processing device acquires an image captured by a transmission electron microscope. The information processing device, for each partial region in the image, executes a two-dimensional Fourier transform on an image of the partial region. The information processing device, based on results obtained by executing the two-dimensional Fourier transform on each of the partial regions, performs clustering of frequency strengths obtained from the results of the two-dimensional Fourier transform. The information processing device determines regions of different crystallinity in the image, based on results of the clustering.

Abstract: A method in a server includes receiving sensor data from an edge computing device, the sensor data generated by a sensor array disposed on a support surface carrying items; detecting, from the sensor data, a set of regions of the sensor array corresponding to respective items carried on the support surface; generating, for each region, a corresponding monitoring definition, each monitoring definition containing: a location of the region within the array, a noise compensation indicator, and an item presence indicator; sending the monitoring definitions to the edge computing device; subsequent to sending the monitoring definitions, receiving item count data from the edge computing device, the item count data derived at the edge computing device from further sensor data generated by the sensor array, based on the monitoring definitions.

Abstract: An image processing apparatus and method are provided. The image processing apparatus acquires a target image including a depth image of a scene, determines three-dimensional (3D) point cloud data corresponding to the depth image based on the depth image, and extracts an object included in the scene to acquire an object extraction result based on the 3D point cloud data.

Abstract: A system for detecting, capturing, analyzing and displaying data for a game using a moving ball and players, whereby the system defines, stores and displays various characteristics of the ball in real time.

Abstract: An image classification method is provided to an electronic device. The method includes: receiving a target image and a reference image about the target image, the target image being a medical image; determining a first image feature of the target image and a second image feature of the reference image; fusing the first image feature and the second image feature to determine a to-be-classified image feature; and determining, by using the to-be-classified image feature, a probability that the target image belongs to a preset category.

Abstract: A method for image combination may include obtaining a first image and a second image; dividing the first image into a plurality of first image blocks and dividing the second image into a plurality of second image blocks; for each of the plurality of first image blocks, determining a first block weight based on edge information of the first image block and determining a second block weight based on overall information of the first image block; for each of the plurality of second image blocks, determining a third block weight based on overall information of the second image block; determining an exposure gain ratio based on the second block weights and the third block weights; determining a first combination weight and a second combination weight based on the exposure gain ratio; generating a third image based on the first combination weights and the second combination weights.

Abstract: In order to extract a foreground area more appropriately, an image processing apparatus for extracting a foreground area from an inputted image includes an image input unit that sets a first area and a second area different from the first area in the inputted image, a first extraction unit that extracts a foreground area from the first area, and a second extraction unit that extracts a foreground area from the second area by using an extraction method different from an extraction method used by the first extraction unit.

Abstract: Systems and methods are disclosed for evaluating cardiovascular treatment options for a patient. One method includes creating a three-dimensional model representing a portion of the patient's heart based on patient-specific data regarding a geometry of the patient's heart or vasculature; and for a plurality of treatment options for the patient's heart or vasculature, modifying at least one of the three-dimensional model and a reduced order model based on the three-dimensional model. The method also includes determining, for each of the plurality of treatment options, a value of a blood flow characteristic, by solving at least one of the modified three-dimensional model and the modified reduced order model; and identifying one of the plurality of treatment options that solves a function of at least one of: the determined blood flow characteristics of the patient's heart or vasculature, and one or more costs of each of the plurality of treatment options.

Abstract: In the multi-target detection and tracking method, lidar (2D laser scanner) scans point cloud data of surroundings and transfers the collected data to the edge server. Then, the edge server uploads the data to the cloud. After obtaining the lidar data, point clouds of footsteps are extracted through dynamic point extraction, point clustering, and random forest model, respectively. Footsteps are matched to form human tracking trajectory by using trajectory matching. After the tracking process, the walking information is published to the users, in a visual form. Meanwhile, the gait parameters are saved into files, including walking speed and step length, when human is detected. Comparing to the visual sensor based human tracking methods, the present invention employs lidar to avoid the interference of ambient light, which leads to easier implementation and larger universality, especially for multi-target scenarios.

Abstract: Aspects of the subject disclosure may include, for example, receiving a plurality of proposed machine learning solutions to a machine learning problem including receiving, for each respective proposed machine learning solution of the plurality of proposed machine learning solutions, one or more of a machine learning model, a dataset and a data pipeline output; automatically determining hybrid solutions to the machine learning problem, including combining, by the processing system, at least one of a first component from a first proposed machine learning solution with at least one of a second component from a second proposed machine learning solution; and ranking the hybrid solutions including determining a log loss score for each hybrid solution and sorting the hybrid solutions according to the log loss score for each hybrid solution. Other embodiments are disclosed.

Abstract: A computer device segments a first sample region to obtain a candidate image region set that includes a plurality of candidate image regions, For each of the candidate image regions, the device obtains a first relationship degree corresponding to each candidate image region and obtains a second relationship degree corresponding to the candidate image region. The device obtains a relationship degree change value based on the first relationship degree and the second relationship degree. The device selects, from the plurality of candidate image regions, a first candidate image region as a target image region in accordance with a determination that the first candidate image region satisfies a condition in the relationship degree change value. The device performs model training based on the target image region to obtain a target detection model.

Abstract: An apparatus for generating a map includes a processor configured to detect a stop line of an intersection from a bird's-eye view image, detect from the bird's-eye view image an intersection area including an intersection and roads connected to the intersection, detect at least either one of an entry lane for entering the intersection and an exit lane for exiting the intersection in a road from which the stop line is extracted, of the roads, based on the ratio of the length of the stop line to the width of the road, and generate a lane network representing a connection relationship between lanes in the intersection so as to connect, for each of the roads, the entry lane of the road to the exit lane of another of the roads to which a vehicle is allowed to proceed from the entry lane of the road.

Abstract: A surgical instrument navigation system and method of use is provided that visually simulates a virtual volumetric scene of a body cavity of a patient from a point of view of a surgical instrument residing in the cavity of the patient, wherein the surgical instrument, as provided, may be a steerable surgical catheter with a biopsy device and/or a surgical catheter with a side-exiting medical instrument, among others. Additionally, systems, methods and devices are provided for forming a respiratory-gated point cloud of a patient's respiratory system and for placing a localization element in an organ of a patient.

Abstract: In order to extract a foreground area more appropriately, an image processing apparatus for extracting a foreground area from an inputted image includes an image input unit that sets a first area and a second area different from the first area in the inputted image, a first extraction unit that extracts a foreground area from the first area, and a second extraction unit that extracts a foreground area from the second area by using an extraction method different from an extraction method used by the first extraction unit.

Abstract: There is achieved short-time measurement of a measurement target such as a farm field with high accuracy. Therefore, processing is performed on a sampling image obtained by the imaging of a part of a range as a measurement target with a multi spectrum camera that performs imaging to capture images in a plurality of different wavelength bands. Then, arithmetic processing is performed on the sampling image as a processing target to generate a calculation result image serving as evaluation information for the entire measurement target.

Abstract: Apparatus detecting driving incapability state of a driver includes: a head detection portion that successively detects a head portion, which is higher than a neck of the driver, based on an image of a driver's seat captured by an imaging device mounted in a vehicle; and an out-of-frame state detection portion that detects that the driver is incapable of driving, when the head portion detected by the head detection portion is out of a predetermined scope in the image during travelling of the vehicle.

Abstract: A method, computer program, and computer system is provided for point cloud coding. The method includes receiving, from a bitstream, data corresponding to a point cloud; obtaining from the data a first prediction residual of a first component from among a plurality of components of an attribute associated with the point cloud; reconstructing the first prediction residual; determining a predicted second prediction residual based on the reconstructed first prediction residual and at least one model parameter; obtaining a second prediction residual of a second component from among the plurality of components based on the predicted second prediction residual; reconstructing the second prediction residual; and decoding the data corresponding to the point cloud based on the reconstructed first prediction residual and the reconstructed second prediction residual.

Abstract: A processor-implemented neural network method includes: determining a respective probability density function (PDF) of normalizing a statistical distribution of parameter values, for each channel of each of a plurality of feature maps of a pre-trained neural network; determining, for each channel, a corresponding first quantization range for performing quantization of corresponding parameter values, based on a quantization error and a quantization noise of the respective determined PDF; determining, for each channel, a corresponding second quantization range, based on a signal-to-quantization noise ratio (SQNR) of the respective determined PDF; correcting, for each channel, the corresponding first quantization range based on the corresponding second quantization range; and generating a quantized neural network, based on the corrected first quantization range corresponding for each channel.