Abstract: A method and system for grading a jewelry item is provided. The method includes: capturing an image of the jewelry item; analyzing the image to identify at least one of: one or more inclusions in the jewelry item, a color of the jewelry item, and one or more dimensions of the jewelry item; evaluating a quality of the jewelry item based on at least a subset of features including: one or more sizes of the one or more inclusions, one or more placements of the one or more inclusions, one or more color characteristics of the one or more inclusions, the color of the jewelry item, the one or more dimensions of the jewelry item, or a combination of the foregoing; and determining a grading of the jewelry item in which the quality of the jewelry item is quantified in relation to additional gradings concerning corresponding additional jewelry items.

Abstract: Technology is described for generating a modified logo using popular colors of a logo file to be used in electronic promotional pages. In addition, options selected by a user, the color of the logo itself and attributes of the electronic promotional pages can be used to filter electronic promotional pages provided. One method may be the operation of detecting a hue, saturation and luminance (HSL) in pixels of a logo file. Another operation may be clustering of the pixels from the logo file into groups based on hue, saturation and luminance (HSL). The colors in the color clusters may be weighted based on area of the logo file occupied by a color. Colors that exceed a defined weighting percentage may be selected as a popular color. Any repeated popular colors may be removed. Then a modified logo may be generated using the popular color selected.

Abstract: The present invention relates to a system and a method for comparing information contained on at least two documents belonging to an entity. The present invention includes at least one device configured to receive information from at least one first document and at least one second document; then, compare at least one first document information and at least one second document information; and determine whether at least one second document contains at least one first document information. The present invention then outputs a result of whether the at least one second document contains at least one first document information.

Abstract: Systems and methods are disclosed for optimizing a sub-sampling pattern for efficient capture of a sub-sampled image to be reconstructed to form a high-resolution image, in a data-driven fashion. For example, Magnetic Resonance Imaging (MRI) scans can be accelerated by under-sampling in k-space (i.e., the Fourier domain). Since the reconstruction model's success depends on the sub-sampling pattern, optimization of the sub-sampling pattern can be combined with optimization of the model, for a given sparsity constraint, using an end-to-end learning operation. A machine-learning model may be trained using full-resolution training data that are under-sampled retrospectively, yielding a sub-sampling pattern and reconstruction model that are customized to the type of images represented in the training data.

Abstract: In one embodiment, a method includes receiving, by a defect detector module, an image of a physical object and classifying, by the defect detector module, one or more first features from the image of the physical object into one or more first classifications using one or more machine learning algorithms. The method further includes analyzing, by the defect detector module, the one or more first classifications and determining, by the defect detector module, that the physical object comprises a defect based on analyzing the one or more first classifications.

Abstract: A management system including at least one processor, wherein the processor is configured to acquire a captured image obtained by imaging an outer surface of each of plural sample containers which contains a sample and in which discrimination information for discriminating a subject from whom the sample is collected is given to the outer surface, and associate a test result related to the sample contained in each of the sample containers with a test order in which information of a discrimination image including the discrimination information is registered in advance for each subject, based on the captured image and the test order.

Abstract: An apparatus configured to be head-worn by a user, includes: a screen configured to present graphics for the user; a camera system configured to view an environment in which the user is located; and a processing unit coupled to the camera system, the processing unit configured to: obtain locations of features for an image of the environment, wherein the locations of the features are identified by a neural network; determine a region of interest for one of the features in the image, the region of interest having a size that is less than a size of the image; and perform a corner detection using a corner detection algorithm to identify a corner in the region of interest.

Abstract: This application provides a data processing method and device. The method includes: collecting a first image by using a camera; obtaining first point cloud data of the object based on the first image, where the first point cloud data indicates three-dimensional coordinate values of a surface point of the object in a first camera coordinate system of the first terminal; obtaining pose data of the first terminal in the first camera coordinate system based on the first image; obtaining a two-dimensional feature image based on the pose data, the first point cloud data, and the first image; generating map data based on the first point cloud data, the pose data, and the two-dimensional feature image; and sending the map data to a second terminal or a server.

Abstract: The information processing apparatus obtains a distribution characteristic representing an attribute of a color included in an acquired first image group and determines the number of times of learning based on the distribution characteristic. The information processing apparatus generates a data set consisting of a set of the first image group and a second image group corresponding to the first image group and by using the generated data set, generates a learning model by performing learning using a network based on the determined number of times of learning.

Abstract: A method for processing a 360-degree image includes determining a processing order of each of a plurality of segments constituting a 360-degree image, based on positions of the segments and parameters of a camera by which the 360-degree image is captured, obtaining distortion correction information according to distortion in the 360-degree image predicted based on parameters of an optical device via which at least a partial region of the 360-degree image is projected, and processing data of the at least a partial region of the 360-degree image according to the determined processing order and the obtained distortion correction information.

Abstract: An object detection processing section 21 detects an object region, using at least one of multiple viewpoint images (e.g., left-viewpoint image) with different viewpoint positions on the basis of information learned through prior learning. A distance measuring section 23 performs ellipse fitting on the object region detected by the object detection processing section 21 to set a distance measurement point arrangement region, and sets multiple distance measurement points in the distance measurement point arrangement region. The distance measuring section 22 performs a stereo matching process using the multiple viewpoint images to calculate a parallax with sub-pixel accuracy for each of the distance measurement points corresponding to the object indicated by an image of the object region and, on the basis of the calculated parallaxes, generates distance measurement information regarding the object.

Abstract: Semi-automated quantitative phenotype analysis of organisms, such as plant organisms, bacterial organisms, and the like. An imaging system, image capture specifications, a semi-automated quantitative image analysis process, and automated batch processing of acquired images that enables completely quantitative experimental readouts that produces data rapidly and objectively.

Abstract: A method of calculating a size of a Gaussian kernel in a crowd counting system. The method includes dividing a crowd density map into several areas at equal intervals; calculating an estimated value of average distance of k nearest heads with respect to a head center point coordinate of a current person; calculating a weight coefficient for an average distance of k nearest heads; calculating a size of a Gaussian kernel corresponding to the head center point coordinate of the current person; determining whether there are any head center point coordinates of which sizes of Gaussian kernels have not been calculated yet in training data. If there are head center point coordinates of which sizes of the Gaussian kernels have not been calculated in the training data, recalculating an estimated value of average distance of k nearest heads with respect to another head center point coordinate of another current person.

Abstract: A method includes obtaining a first image to be rendered, obtaining a target mask image corresponding to the first image where a g component of the target mask image stores first light change data and a b component of the target mask image stores second light change data, the first light change data being change data of light on a left side of the first image used when the first image is rendered and the second light change data being change data of light on a right side of the first image used when the first image is rendered, and rendering the first image by using the target mask image to obtain a second image.

Abstract: The present disclosure relates to the technical field of growth environment control for plants, and provides a light regulation method, system, and apparatus for a growth environment of leafy vegetables. The method includes: obtaining a growth environment image and growth environment light parameters of leafy vegetables; inputting the growth environment image into an image segmentation model to obtain an initial pixel segmentation map; determining a leaf area of the leafy vegetables according to the initial pixel segmentation map by using a Class Activation Mapping (CAM)-K algorithm; inputting the leaf area and the growth environment light parameters of the leafy vegetables into a leafy vegetable growth index prediction model to obtain a growth index of the leafy vegetables; adjusting the growth environment light parameters according to the growth index of the leafy vegetables. This disclosure achieves automated and intelligent control of light conditions in the growth environment of leafy vegetables.

Abstract: The present invention relates to a three-dimensional reconstructing method of a 2D medical image. A three-dimensional reconstructing device includes: a communicator for receiving sequential 2D images with an arbitrary slice gap; a sliced image generator for generating at least one sliced image positioned between the 2D images based on a feature point of the adjacent 2D images; and a controller for reconstructing the 2D image into a 3D image by use of the generated sliced image and providing the 3D image.

Abstract: Provided are a vibration object monitoring method and apparatus, a computer device, and a storage medium. The method includes: in response to detecting that a vibration object exists in a monitoring video picture for a target monitoring region, a vibration object region in the monitoring video picture is determined, where the vibration object region is a region where the vibration object is located in the monitoring video picture; displacement information of a key point of the vibration object in the vibration object region is recorded; vibration information of the vibration object in the monitoring video picture is determined based on the displacement information; and a vibration object monitoring result for the target monitoring region is generated according to the vibration information. The abnormal vibration monitoring can be performed on the vibration object in the target monitoring region in time according to this method.

Abstract: Provided is a binarization method for CT sectional image of fiber package containing artifacts, which includes: performing brightness adjustment on the source image obtained after converting of the HSV image model by using a composite tangent function; creating a planar morphological structural element having a morphology similar to that of a target object to obtain a background image without the target object; obtaining a second intermediate image by a subtraction operation of the first intermediate image and the background image; improving an image contrast of the second intermediate image again to obtain a third intermediate image; and binarizing the third intermediate image by using a local adaptive threshold binarization algorithm and removing a background noise to obtain a final binarized image. The binarization method can improve the uneven brightness of the image under complex illumination, alleviate the artifacts, and strip similar objects from the background with similar gray scales.

Abstract: Disclosed is a cell classification method, to be executed by an analyzer, for classifying cells contained in a specimen, including: preparing a first measurement sample by treating a specimen under a first preparation condition; obtaining a first signal from the prepared first measurement sample; classifying, by using the first signal, cells contained in the first measurement sample; preparing a second measurement sample by treating the specimen under a second preparation condition different from the first preparation condition; obtaining a second signal from the prepared second measurement sample; classifying, by using the second signal, cells contained in the second measurement sample; and comparing a result of the cell classification performed by using the first signal and a result of the cell classification performed by using the second signal, with each other, and outputting an analysis result including a number of cells on the basis of a result of the comparison.

Abstract: Systems and methods for determining bacterial load in targets are disclosed. An autofluorescence detection and collection device includes a light source configured to illuminate a target with excitation light causing at least one biomarker in the illuminated target to fluoresce. Bacterial autofluorescence data regarding the target is collected and analyzed to determine bacterial load the target. The autofluorescence data may be analyzed using pixel intensity.