Abstract: A sequence of images depicting an object is captured, e.g., by a camera at a point-of-sale terminal in a retail store. The object is identified, such as by a barcode or watermark that is detected from one or more of the images. Once the object's identity is known, such information is used in training a classifier (e.g., a machine learning system) to recognize the object from others of the captured images, including images that may be degraded by blur, inferior lighting, etc. In another arrangement, such degraded images are processed to identify feature points useful in fingerprint-based identification of the object. Feature points extracted from such degraded imagery aid in fingerprint-based recognition of objects under real life circumstances, as contrasted with feature points extracted from pristine imagery (e.g., digital files containing label artwork for such objects).

Abstract: The present technology pertains to influencing the blending of two visual media inputs by first receiving them through a prompt editor. A blending interface is presented, displaying at least one frame from each of the first and second input visual media. The blending is adjusted in response to user input by modifying a blend curve that represents the relative influence of the first visual media compared to the second visual media over time.

Abstract: In a method of image model processing, an image model is acquired, the image model includes a first feature reconstruction module configured to extract feature information of training data, the first feature reconstruction module includes at least two branches. Reconstruction processing based on merging is performed on the at least two branches of the first feature reconstruction module to obtain a second feature reconstruction module, the second feature reconstruction module has a reduced number of branches compared to the first feature reconstruction module, and the second feature reconstruction module is configured to extract feature information of a to-be-processed image. The first feature reconstruction module in the image model is replaced with the second feature reconstruction module to obtain an optimized image model, the optimized image model is configured to perform image quality enhancement processing on the to-be-processed image.

Abstract: Embodiments of the present disclosure provide a method for optimizing a base image library, an apparatus for optimizing a base image library, an electronic device, and a storage medium. The method includes: determining a first base image and a plurality of second base images from the base image library; calculating a difference between the first base image and each of the plurality of second base images respectively, and obtaining a plurality of residual images based on the calculation result; and deleting, in response to determining based on the plurality of residual images that shading interference is present in the first base image, the first base image from the base image library. The method for optimizing a base image library provided in the present disclosure can delete base images with shading interference from the base image library, and can improve the accuracy of fingerprint identification by the fingerprint sensor.

Abstract: This disclosure provides methods, devices, and systems for color volume mapping (CVM) techniques that operate in the Jzazbz color space. In some aspects, an image processor may receive image data having color channels associated with a color space that is not perceptually uniform and may convert the image data to the Jzazbz color space. The image processor may perform a global CVM operation which maps a range of Jz, az, and bz values supported by the image source to a range of jz, az, and bz values supported by the image target. The image processor may further perform a local CVM operation which adaptively tunes the Jz, az, and bz channels of image data based on various properties of the received image. Still further, the image processor may adaptively blend Jz values at the edges of objects and other features to preserve details in low-contrast regions of the received image.

Abstract: A method and electronic device are provided for providing a high dynamic range (HDR) image.

Abstract: A method for cable wire insertion verification includes receiving, from a camera system, an inspection image of a connector housing held in a housing retainer of a housing inspection system. Via a connector recognition machine vision system, the connector housing is classified as a recognized connector housing type based, at least in part, on a comparison between the inspection image of the connector housing and a template image corresponding to the recognized connector housing type. For one or more cable cavities of the connector housing, the method includes automatically verifying whether a correct cable wire is inserted into the cable cavity according to the recognized connector housing type.

Abstract: A method of repairing a defect on a surface is presented that includes imaging the surface to locate the defect with a first imaging system. The method also includes conducting a repair operation by contacting the surface with an abrasive article. The abrasive article is pressed into contact with the surface in an area of the defect by a robotic repair system. The method also includes imaging the abraded surface, with a second imaging system. Imaging includes scanning the surface in the defect area to obtain a topography of the defect area, passing the second imaging system over the defect area such that a distance between the second imaging system and the surface is maintained. Imaging also includes generating an image of the defect area, wherein the image is a near dark field image or a dark field image and generating an evaluating regarding the repair operation based on the generated image.

Abstract: According to one embodiment, a normal vector set creation apparatus generates a feature vector for each position of a normal image by performing feature amount extraction processing using a neural network on the normal image, generates position information indicating whether or not a feature vector at each position of the normal image is an acquisition target by performing image processing on the normal image, selects a feature vector of the acquisition target from among the generated feature vectors based on the position information, and stores the selected feature vector of the acquisition target as a normal vector.

Abstract: A measurement device includes the following: a time-series signal obtaining unit configured to obtain a biological signal, which is time-series data of a biological signal value calculated from an image captured by imaging a living body, and obtain a determination index for the image; a biological-information calculating unit configured to divide the biological signal into pulse signals at predetermined times based on the cycle of a biological phenomenon; and a pulse determining unit configured to adopt pulse signals including biological signal vales calculated from the image that enables a determination index satisfying a determination condition to be calculated. The biological-information calculating unit calculates biological information by using the pulse signals adopted by the pulse determining unit.

Abstract: An apparatus and method for training and using a computing operation for digital image processing are provided. The apparatus and method may be used for 3-dimensional medical images. An exemplary method for digital image processing comprises: receiving an image displaying at least one detectable structure, determining the detectable structure; segmenting the image to obtain a segmentation mask that is associated with a geometric shape and comprises at least one quantifiable visual feature; generating a mesh based on the quantifiable visual feature; computing at least on quantifiable visual parameter based on the mesh; extracting quantifiable visual data from the image based on the quantifiable visual parameter; training the computing operation with the quantifiable visual data.

Abstract: The present disclosure provides a system (100) of identifying a plurality of parameters related to abnormalities in a subject's skin. The system (100) comprises a scanner (110), a remodeling processor, a control unit (120), a prediction processor, one or more energy projecting systems (140) and a touch-screen panel (130). The scanner (110) is configured to scan a 2D image of the subject's skin from multiple angles to capture one or more feature points. The remodeling processor is configured to construct a 3D model of the subject's skin. The control unit (120) comprising a prediction processor configured to determine a first set of parameters and a second set of parameters and the plurality of parameters. The touch-screen panel (130) is configured to display the plurality of parameters to a physician/user.

Abstract: Methods and systems for implementing artificial intelligence enabled metrology are disclosed. An example method includes segmenting a first image of structure into one or more classes to form an at least partially segmented image, associating at least one class of the at least partially segmented image with a second image, and performing metrology on the second image based on the association with at least one class of the at least partially segmented image.

Abstract: Systems and methods for re-identifying tracked subjects in an area of real space are disclosed. The method includes generating first and second reidentification feature vectors of a first subject identified from a first time interval from the respective first and second sequences of images as obtained from the first time interval, and generating third and fourth reidentification feature vectors of a second subject identified from a second time interval from the respective first and second sequences of images. The method includes calculating a first similarity score between the first and third reidentification feature vectors, and calculating a second similarity score between the second and fourth reidentification feature vectors. The method includes matching the second subject to the first subject when at least one similarity score is above a pre-defined threshold.

Abstract: A target recognition system recognizes a target shown in an image captured by an infrastructure camera. The target recognition system detects a first target shown in the image as a temporary target. When a class of the temporary target is a movable target, the target recognition system applies a tracking process to the temporary target and determines that the first target is a real movable target based on a result of detection of the temporary target in a first period. When the class of the temporary target is a stationary target, the target recognition system determines that the first target is a real stationary target based on a result of detection of the temporary target in a second period without applying the tracking process to the temporary target.

Abstract: Inferences may be obtained to handle access requests at a non-relational database system. An access request may be received at a non-relational database system. The non-relational database system may determine that the access request uses a machine learning model to complete the access request. The non-relational database system may cause an inference to be generated using data items for the access request as input to the machine learning model. The access request may be completed using the generated inference.

Abstract: Embodiments of the disclosed technologies include receiving a first query including at least one first query term and configuring at least one prompt to cause a large language model to translate the at least one first query term into a set of functions that can be executed to obtain at least one second query term and generate and output a plan that is executable to create a modified version of the first query based on the at least one second query term. The plan is obtained by applying the large language model to the at least one prompt as configured. The plan is executed to determine the at least one second query term and create the modified version of the first query. The modified version of the first query is executed to provide, via the user interface, a response to the first query.

Abstract: Example embodiments of the present disclosure provide for an example method including obtaining component data associated with a plurality of components. The example method includes generating an index of the component data and obtaining user input data indicative of a request. The example method includes processing the user input data to determine an intent associated with the request and obtaining, based on the intent, data indicative of one or more components from the index. The example method includes determining a rank for at least one respective component of the one or more components. The example method includes updating a user interface to display the one or more components, wherein the components are displayed based at least in part on the rank of the respective component. The example method can include generating modular spaces composed of a plurality of components to generate composite application interfaces which can include cross-application functionalities.

Abstract: Embodiments of the present invention relate to a distributed self-contained communications system (dSCCS). The dSCCS includes primary computing devices (PCDs) and secondary computing devices (SCDs). The PCDs and SCDs are man-portable. Each PCS includes a communications device. Each SCD includes geolocation device and a unique digital identifier. The PCDs form a mesh network. Each PCD communicates with a SCD via a LAN. Each SCD transmits their geospatial data and unique identifier to a PCD. Each PCD transmits the geospatial data and unique identifiers to a command node included in the mesh network. The PCD and/or the command node is configured to map the geospatial data and the unique identifier to Earth coordinates in real-time or at predetermined intervals. Each PCD and SCD includes an antenna element that includes graphene dispersed in a polymer. Each SCD includes a heatsink and thermal dissipation structure.

Abstract: The present disclosure relates to systems and methods for retrieving telematics data.