Abstract: An artificial intelligence (AI) decoding method including obtaining image data generated from performing first encoding on a first image and AI data related to AI down-scaling of at least one original image related to the first image; obtaining a second image corresponding to the first image by performing first decoding on the image data; obtaining, based on the AI data, deep neural network (DNN) setting information for performing AI up-scaling of the second image; and generating a third image by performing the AI up-scaling on the second image via an up-scaling DNN operating according to the obtained DNN setting information. The DNN setting information is DNN information updated for performing the AI up-scaling of at least one second image via joint training of the up-scaling DNN and a down-scaling DNN used for the AI down-scaling.

Abstract: An imaging system, comprising a shooting operation interface that operates to form an image of a subject, and a processor that has a bio-information acquisition section and a stress determination section, wherein the bio-information acquisition section acquires bio-information of an operator when, during shooting awaiting action where an instant for acquiring still images is awaited, the shooting operation interface is operated, and the stress determination section determines stress conditions that shooting actions place on the operator based on the bio-information that has been acquired using the bio-information acquisition section.

Abstract: Systems for delivering one or more studies, where each of the one or more studies has a series of digital images associated with only one person and generated by an imaging modality, is disclosed. The systems include a syncing application that is configured to execute within a local area network and that is in data communication with imaging modalities and/or computing devices configured to display images generated by each of the imaging modalities. The systems also include a server adapted to be external to the local area network and in data communication with the syncing application and a client-side viewing application installed on one or more of the computing devices. The client-side viewing application is configured to acquire the studies, including unrendered data representative of the digital images of the series, locally render the unrendered data, and enable a user to manipulate the digital images.

Abstract: The present disclosure is related to systems and methods for orthosis design. The method includes obtaining a three-dimensional (3D) model associated with a subject. The method includes obtaining one or more reference images associated with the subject. The method includes determining, based on the 3D model and the one or more reference images, orthosis design data for the subject. The orthosis design data may be used to determine an orthosis for the subject.

Abstract: Techniques related to generating holographic images are discussed. Such techniques include application of a machine learning model to the target image to generate data that is used to enable the determination of a phase pattern via a wave propagation model. The wave propagation model is used to generate holographic data, which is then adjusted according to one or more constraints associated with the holographic display that will be used to generate a holographic image based on the adjusted holographic data.

Abstract: A method for detecting boxes includes receiving a plurality of image frame pairs for an area of interest including at least one target box. Each image frame pair includes a monocular image frame and a respective depth image frame. For each image frame pair, the method includes determining corners for a rectangle associated with the at least one target box within the respective monocular image frame. Based on the determined corners, the method includes the following: performing edge detection and determining faces within the respective monocular image frame; and extracting planes corresponding to the at least one target box from the respective depth image frame. The method includes matching the determined faces to the extracted planes and generating a box estimation based on the determined corners, the performed edge detection, and the matched faces of the at least one target box.

Abstract: In one embodiment, a method includes, by a computing system, accessing a first and second texture associated with an output position, determining a color-blending operation, determining a first color and a first transparency level based on the first texture, determining a second color and a second transparency level based on the second texture, and identifying a color-blending optimization based on the color-blending operation and a comparison of the colors and transparency levels. The method includes determining an output color and an output transparency level by performing the color-blending operation using the colors and transparency levels. The output color is determined by copying the first or second color or the output transparency level is determined by copying the first or second transparency level without additional calculation. The method includes providing the output color and the output transparency level for display at the output position.

Abstract: An inspection device that inspects eligibility of a subject image, the inspection device including a hardware processor and a recording medium including instructions that when executed by the hardware processor cause the inspection device to: acquire the subject image and a reference image corresponding to the subject image; acquire a judgment criterion indicating a range of eligibility for differences between images; detect a difference between the subject image and the reference image; and when the difference is detected, judge eligibility of the subject image by determining whether or not the difference is included in the range indicated by the judgment criterion.

Abstract: A method, apparatus, and computer-readable medium for point cloud coefficient coding are provided. Transform coefficients associated with point cloud data are decomposed into set-index values and symbol-index values, the symbol index-value specifying location of the transform coefficient within a set. The decomposed transform coefficients are partitioned into one or more sets based on the set-index values and the symbol-index values. The set-index values of the partitioned transform coefficients are entropy-coded, and the symbol-index values of the partitioned transform coefficients are bypass-coded. The point cloud data is compressed based on the entropy-coded symbol-index values and the bypass-coded set-index values.

Abstract: Systems and methods for viewing, storing, transmitting, searching, and editing application-specific audiovisual content (or other unstructured data) are disclosed in which edge devices generate content on the fly from a partial set of instructions rather than merely accessing the content in its final or near-final form. An image processing architecture may include a generative model that may be a deep learning model. The generative model may include a latent space comprising a plurality of latent codes and a trained generator mapping. The trained generator mapping may convert points in the latent space to uncompressed data points, which in the case of audiovisual content may be generated image frames. The generative model may be capable of closely approximating (up to noise or perceptual error) most or all potential data points in the relevant compression application, which in the case of audiovisual content may be source images.

Abstract: At least two images are acquired. At least two crop images are acquired by cropping the at least two images for face-containing images. Triangular patch deformation is performed on two neighbour images, generating a first triangular patch deformation frame image sequence and a second triangular patch deformation frame image sequence. Similarity transformation is performed on each image sequence of the first triangular patch deformation frame image sequence, acquiring a first transform frame image sequence. Similarity transformation is performed on each image sequence of the second triangular patch deformation frame image sequence, acquiring a second transform frame image sequence. The first and the second transform frame image sequences are fused, acquiring a video frame sequence corresponding to the two neighbour images. Of the at least two images, a video frame sequence generated by all neighbour images is coded, acquiring a destined video.

Abstract: A method for visualizing a large-scale point cloud based on normal, including: (S1) according to a spatial structure of a point cloud data, constructing a balanced octree structure of a node point cloud; (S2) according to the balanced octree structure and normal information of a point cloud, constructing an octree structure with the normal information; and constructing a normal level-of-detail (LOD) visualization node through downsampling; and (S3) determining a node scheduling strategy according to a relationship between a viewpoint, a viewing frustum and a normal of a render node; and respectively calling a reading thread and a rendering thread to simultaneously perform reading and rendering according to the node scheduling strategy.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for escape detection and mitigation for aquaculture. In some implementations, a method includes obtaining one or more images that depict one or more fish within an enclosure; generating, as a result of providing the one or more images to multiple detection models, a value that reflects a quantity of fish that are depicted in the images that are likely a member of each different type of fish; detecting an error condition relating to a possible opening of the enclosure based at least on the value; and in response to detecting the error condition relating to the possible opening of the enclosure, initiating one or more mitigation actions relating to the possible opening.

Abstract: An image processing apparatus comprising, a first processing unit configured to process a first image stored in a first memory and output a first processing result in a first size, a conversion unit configured to, if the first size matches a second size, output the first processing result, and if the first size is different from the second size, convert the first processing result into the second size and output a result of the conversion, and a second processing unit configured to process the first processing result outputted from the conversion unit and a second image of the second size stored in a second memory, and to store a second processing result in the second memory in the second size.

Abstract: A method to reconstruct an environment is provided. The method makes available to a wide variety of XR applications fresh and accurate 3D reconstruction data of environments with low processing time and low usage of computational resources and storage spaces. The 3D reconstruction data are structured in a way to be efficiently shared between users for multi-user experiences. The method includes obtaining plane segments of an environment, identifying surface planes of the environment by, for example, filtering and grouping the plane segments or ad hoc selection of the plane segments by a user, and inferring corner points of the environment based on the surface planes. The corner points are used to build a 3D representation of the environment when an XR application requires.

Abstract: A method and apparatus for method for image processing, and a computer storage medium are provided. The method includes: obtaining a first image, identifying a target object in the first image, and obtaining leg detection information of the target object; respectively determining a contour line and a target line of a leg region of the target object based on the leg detection information; and performing image deformation processing on the leg region based on the contour line and the target line of the leg region to generate a second image.

Abstract: An image processing method performed by a terminal is provided. A molybdenum target image is obtained, and a plurality of candidate regions are extracted from the molybdenum target image. In the molybdenum target image, a target region is marked in the plurality of candidate regions by using a neural network model obtained by deep learning training, a probability that a lump comprised in the target region is a target lump being greater than a first threshold, a probability that the target lump is a malignant tumor being greater than a second threshold, and the neural network model being used for indicating a mapping relationship between a candidate region and a probability that a lump comprised in the candidate region is the target lump.

Abstract: Systems, apparatuses, and methods for implementing automatic data format detection techniques are disclosed. A graphics engine receives data of indeterminate format and the graphics engine predicts an organization of the data. As part of the prediction, the graphics engine predicts the pixel depth (i.e., bytes per pixel (BPP)) and format separately. The graphics engine folds the data along pixel and channel boundaries to help in determining the pixel depth and format. The graphics engine scores modes against each other to generate different predictions for different formats. Then, the graphics engine generates scores for the predictions to determine which mode has a highest correlation with the input data. Next, the graphics engine chooses the format which attains the best score among the scores that were generated for the different modes. Then, the graphics engine compresses the unknown data using the chosen format with the best score.

Abstract: The present invention relates generally to a system and method for measuring the structural characteristics of an object. The object is subjected to an energy application processes and provides an objective, quantitative measurement of structural characteristics of an object. The system may include a device, for example, a percussion instrument, capable of being reproducibly placed against the object undergoing such measurement for reproducible positioning. The invention provides for a system and methods for analyzing measured characteristics utilizing machine learning to create a system for predicting pathologies from measurements.

Abstract: A method of image conversion includes selecting a set of pixels from a source image, storing the set of pixels in a memory, determining whether the set of pixels includes at least one pixel requiring coordinate conversion by querying a predetermined mapping table, if the set of pixels includes the at least one pixel requiring coordinate conversion, converting the coordinates of the at least one pixel, and after converting the coordinates of the at least one pixel, removing the set of pixels from the memory.