Abstract: A method, apparatus, and computer-readable medium for point cloud coefficient coding are provided. The method may include receiving compressed point cloud data based on set-index values and symbol-index values; and entropy-decoding the set-index values based on the compressed point cloud data. The symbol-index values may be bypass-decoded based on the compressed point cloud data, and the set-index values and symbol-index values may be combined into transform coefficients associated with cloud point data.

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 an iterative propagation feedback model. The iterative propagation feedback model is used to generate a feedback strength value, which is then used to generate a phase diffraction pattern for presentation at a holographic plane.

Abstract: Disclosed are an object detection method and a convolution neural network. The method is performed through hierarchical architecture of the CNN and includes extracting groups of augmented feature maps from an input image through a backbone and two other groups of feature maps, identifying positive and negative samples with an IOU-based sampling scheme to be proposals for foreground and background through a proposal-sampling classifier, mapping the proposals to regions on the groups of augmented feature maps through the region proposal module, pooling the regions to fixed scale feature maps based on ROI aligning, fusing the fixed scale feature maps, and flattening the fused feature maps to generate an ROI feature vector through an ROI aligner for object classification and box regression. Because extracted features in the groups of augmented feature maps range from spatially-rich features to semantically-rich features, enhanced performance in object classification and box regression can be secured.

Abstract: This invention is a system and method for utilizing artificial intelligence to operate a surgical robot (e.g., to perform a laminectomy), including a surgical robot, an artificial intelligence guidance system, an image recognition system, an image recognition database, and a database of past procedures with sensor data, electronic medical records, and imaging data. The image recognition system may identify the tissue type present in the patient and if it is the desired tissue type, the AI guidance system may remove a layer of that tissue with the end effector on the surgical robot, and have the surgeon define the tissue type if the image recognition system identified the tissue as anything other than the desired tissue type.

Abstract: Techniques performed by a data processing system for analyzing the impact of training data changes on a machine learning model herein include training a first instance of a machine learning model with a first set of training data; modifying the first set of training data to produce a second set of training data; training a second instance of the model with the second set of training data; comparing the first instance of the model to the second instance of the model to determine features that differ between the first instance and the second instance of the model; identifying a subset of historical data associated with the features that differ between the first instance and the second instance of the model; and scoring the subset of the historical data to produce a report identifying differences in the output of the first instance and the second instance of the machine learning model.

Abstract: The invention relates to a method for a computer device, for detecting an optimal candidate compound based on a plurality of samples comprising a cell line and one or more biomarkers, and a plate map configuration, wherein the plate map configuration is providing locations of samples comprising cell lines exposed to one or more biomarkers and different concentrations of a candidate compound forming at least one concentration gradient, the candidate compound being comprised in a plurality of candidate compounds, said method comprising generating (310) phenotypic profiles of each concentration gradient of each of the plurality of candidate compounds at a plurality of successive points in time to form a plurality of compound profiles, wherein generating phenotypic profiles comprises the steps obtaining (312) image data depicting each sample comprised in the concentration gradient, generating (314) a class-label and a class for each cell of the samples based on the image data, detecting (320) the optimal candidat

Abstract: Systems, apparatuses and methods may provide for technology that decodes data via an instruction that indicates a number of rulebooks to be processed, an input feature size, an output feature size, and a plurality of feature map base addresses, rearranges spatially distributed voxel output feature maps in the decoded data based on weight planes, and performs a channel-wise multiply-accumulate (MAC) operation on the rearranged spatially distributed voxel output feature maps to obtain an output, wherein the channel-wise MAC operation is performed as partial accumulations by a plurality of processing elements.

Abstract: Disclosed are systems, apparatuses, and methods to determine, communicate, and/or respond to state information of at least one of a suspended load control apparatus, carrier, or load suspended by a cable from the carrier, wherein response to the state information may be to control at least one of the suspended load control apparatus, carrier, or load suspended by a cable from the carrier.

Abstract: An image processing apparatus according to an aspect of the present disclosure includes an optical character recognition (OCR) unit configured to sequentially execute processing related to OCR on image data on a plurality of documents, a generation unit configured to select one of the plurality of documents subjected to the processing related to OCR, and to generate a recommendation content about an index to be assigned to the one selected document based on an index extraction rule, and a confirmation unit configured to present the generated recommendation content to a user and to assign an index to the one document based on an instruction from the user. The processing to be executed by the OCR unit and processing to be executed by the confirmation unit are executed in parallel.

Abstract: A method and apparatus for vascular assessment are disclosed. The apparatus, in some embodiments, receives, from a medical imaging device, a medical image of a coronary vessel tree of a subject and calculates a plurality of geometric measurements associated with individual portions of a vascular segment of the coronary vessel tree. The apparatus also determines a plurality of resistances associated with the plurality of geometric measurements associated with the individual portions of the vascular segment and determines a plurality of pressure drops across the individual portions of the vascular segment based on the determined resistances and a calculated or estimated blood flow. The apparatus further calculates based on the plurality of pressure drops, a functional index indicative of a presence or an absence of a stenosis within the vascular segment.

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: 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: 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: 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.