Abstract: A single-instruction, multiple data processor performs object detection in an image by testing for a plurality of object features in a plurality of image regions, the processor comprising: a set of computation units operable to execute a plurality of classifier sequences in parallel, each classifier sequence comprising a plurality of classifier routines, and each classifier routine comprising identical instructions to the other classifier routines in each of the plurality of classifier sequences; wherein each computation unit is configured to independently maintain data identifying an image region and a feature under test on that computation unit, and each classifier routine is arranged to access the data, test the identified feature against the identified image region and update the data such that the computation units are operable to concurrently test different features against different image regions.

Abstract: A target tracking method is provided for a computer device. The method includes determining a target candidate region of a current image frame; capturing a target candidate image matching the target candidate region from the current image frame; determining a target region of the current image frame according to an image feature of the target candidate image; determining motion prediction data of a next image frame relative to the current image frame by using a motion prediction model and according to the image feature of the target candidate image; and determining a target candidate region of the next image frame according to the target region and the motion prediction data.

Abstract: Systems and methods for analyzing trends in image data is disclosed. A trend query is received relating to an object category and defining two or more groups of interest for which trend data is to be determined with a defined time period. Visual tokens of interest are identified relating to the object category for use in searching a token database. One or more image data sets are identified that are associated with each of the two or more groups of interest. Visual tokens are analyzed matching the visual tokens of interest that are associated with the identified image data sets to generate trend data for each of the two or more groups of interest for the defined period of time. An output is generated based on a comparison of the trend data generated for the two or more groups of interest for the defined period of time.

Abstract: This electronic endoscope system includes an evaluation value calculation unit, an assessment unit, and a representative value determination unit. The evaluation value calculation unit is configured so as to obtain an evaluation value indicating an extent of a lesion in biological tissue in each of a plurality of images captured in a predetermined section along the depth direction of a region in an organ. The assessment unit is configured so as to assess whether the extent of the lesion in the section is changed on the basis of the degree of variation of the evaluation value. The representative value determination unit is configured so as to define a representative value of the section representing the evaluation value, in a different method when the extent of the lesion is assessed to be changed and when the extent of the lesion is assessed not to be changed.

Abstract: A method for detection and pathological classification of polyps via colonoscopy based on an anchor-free technique includes: performing feature extraction on a color endoscopic image that is pretreated, enhancing and extending the extracted features, decoding the feature information of the enhanced feature and the extended feature through an anchor-free detection algorithm to acquire a polyp prediction box and a prospect prediction mask, then respectively extracting global and local feature vectors from the extended feature and the prospect prediction mask, and combining the global feature vector with the local feature vector, so as to predict the type of polyps through a full-connection layer. Through the present application, the type of polyps can be correctly predicted, and the detection rate of polyps and the accuracy rate of pathological classification are improved.

Abstract: Apparatus and methods for determining information about one or more objects in a 3-dimensional (3D) space are disclosed. One aspect of the method includes defining a virtual ground plane within a monitored 3D space. The virtual ground plane is divided into a plurality of bins. Each bin has corresponding counter value. An object is detected in a respective image captured by each of a plurality of sensors. A respective line segment is selected corresponding to a respective light between each of the plurality of image sensors and the detected object. One or more bins of the virtual ground plane are selected onto which a respective projected line segment of each respective line segment overlap. Each counter value for each of the one or more selected bins is increased. A location of the object is determined based on a bin of the one or more bins having a highest counter value.

Abstract: A front-end image acquisition component acquires photographs and/or videos of the exterior of a vehicle traveling on a path between a first predefined location and a second predefined location. In one aspect, an image acquisition system comprises a first camera support structure, a second camera support structure, an image processor, and a memory. Cameras are affixed to each of the camera support structures for acquiring image data of a subject vehicle. Image data is controlled by the image processor and the memory. In another aspect, an image acquisition system comprises a first camera tower, a second camera tower, a camera boom. Cameras are affixed to each of the camera towers.

Abstract: A parallel presentation system includes computer hardware including a parallel presentation platform (PPP) connected to an extended reality (XR) system associated with a user. The computer hardware is configured to perform the following operations. A lookup point associated with the user is identified by the PPP. The PPP determines that the user has shifted focus from a first data stream to a second data stream. A shift time associated with the shift along with an identification of the first data stream is stored by the PPP in association with the user. A summarization of the first data stream is generated using a summarization engine of the PPP and the summarization is based upon the shift time and the lookup point. The summarization is forwarded by the PPP to the XR system. Information regarding the summarization is configured to be parallel-presented by the XR system associated with the user.

Abstract: Technology described herein includes a method that includes obtaining an image of a fluid of a microfluidic analysis system. The microfluidic analysis system includes or receives a container that contains the fluid for measurement of analyte or quality determination. A region of interest (ROI) is identified based on the image. The ROI is a set of pixel values for use in the measurement of the analyte or the quality determination of the fluid, fluidic path, or measuring system. Identifying the ROI includes: determining an alignment of the container of the fluid with the imaging device based on the image, and identifying the ROI based on information about the measurement of the fluid or based on information about non-analyte features of the fluid. An analysis of the image of the fluid is performed using the set of pixel values of the ROI.

Abstract: Technologies for summarizing tax documents that include an unstructured portion, such as K1 filings. The system extracts data from both the structured information, such as a K1 facepage, and unstructured information, such as whitepaper statement(s). The system includes machine learning model(s) to determine the information to be extracted from the unstructured information. The machine learning model(s) generate a confidence level associated with the extracted unstructured information that represents a prediction on how likely the extracted unstructured information was accurately extracted. The system generates a document in an electronic interchange format that represents both the structured and unstructured information in the analyzed tax document.

Abstract: A feature point detection apparatus for detecting feature points in image data includes an image data providing unit for providing the image data, a key point determination unit for determining key points in the image data, a feature determination unit for determining features associated with the key points, each describing a local environment of a key point in the image data, and a feature point providing unit for providing the feature points. A feature point is represented by the position of a key point in the image data and the associated features. The image data comprise intensity data and associated depth data, and the determination of the key points and the associated features is based on a local analysis of the image data in dependence on both the intensity data and the depth data.

Abstract: A method for building a robust classifier against evasion attacks includes receiving an application, identifying one or more features of the application, and determining a first confidence score for a first version of the application including a first set of features and determining a second confidence score for a second version of the application including a second set of features, the first set of features is different than the second set of features. The method also includes determining a difference between the first confidence score and the second confidence score, and comparing the difference with a convergence threshold. The method includes, based on the comparison, determining whether the first confidence score exceeds a confidence score threshold, and generating a report based on determining the first confidence score exceeds the confidence score threshold.

Abstract: The described implementations enable a seller to sell items through multiple e-commerce channels without having to maintain independent merchant accounts at each channel. For example, a seller may sell items directly and through a management service. When a user request to purchase an item from the seller through the management service is received, the management service sends the purchase information to the seller so that the seller can complete the purchase as if the purchase were being made directly with the seller. Upon completion of the purchase, the seller provides a confirmation back to the management service and provides the item directly to the user.

Abstract: A distributed data integration device includes an acquisition unit configured to acquire, for a piece of analysis target data, an anchor data intermediate representation and an analysis target intermediate representation, the anchor data intermediate representation being an intermediate representation obtained by converting anchor data by a first function, the anchor data being data commonly used in integration of a plurality of the pieces of analysis target data that are distributed, the analysis target intermediate representation being an intermediate representation obtained by converting the analysis target data by the first function, an anchor data conversion unit configured to convert, for the piece of analysis target data, a plurality of the anchor data intermediate representations by a second function, a calculation unit configured to calculate, for the piece of analysis target data, the second function that minimizes a difference between the plurality of the anchor data intermediate representations, a

Abstract: An image inspection apparatus includes a designated area acquisition device that acquires information related to an area designated in a recording medium, wherein when trial printing is instructed, a read image of an image printed on the recording medium in the trial printing and an image of the area generated on the basis of the information related to the area acquired by the designated area acquisition device are combined.

Abstract: In some aspects, the disclosure is directed to methods and systems for automatic context-based annotation by leveraging a priori knowledge from annotations in template documents. A large library of template documents may be generated and pre-processed in many implementations to identify annotations or other inclusions commonly present on documents related to or conforming to the template. Newly scanned documents may be compared to these templates, and when a similar template is identified, annotation locations and types from the template may be applied to the newly scanned document to recognize and classify annotations and inclusions. To increase efficiency and provide scalability, comparisons of scanned documents and template documents may be distributed amongst a plurality of computing devices for processing in parallel, with similarity results aggregated.

Abstract: An abnormality detection apparatus is provided. The abnormality detection apparatus includes a first generation part configured to generate pseudo-abnormal image data by synthesizing a substantially circular image at a random position of an image of normal image data obtained by photographing equipment that includes a liquid supply and supplies a liquid from the liquid supply without an abnormality, a second generation part configured to generate a determination model for determining whether the equipment is normal or abnormal by performing learning of the normal image data and the pseudo-abnormal image data, an acquisition part configured to acquire image data obtained by photographing the equipment, and a detection part configured detect an abnormality in the equipment from the image data acquired by the acquisition part using the determination model.

Abstract: Systems and methods for image-based item identification are disclosed. Image data corresponding to one or more images depicting an item may be sent to one or more remote systems for image-based item identification. The identification indications and/or identification confidence scores received from the remote systems may be aggregated and weighted based at least in part on one or more factors related to the remote systems, the results, domains, image capture timing, image capture angles, and/or events to more accurately identify an item depicted in the images.

Abstract: A computer implemented method transforms data. Responsive to receiving a data transformation of an input string to an output string, a computer system identifies mappable tokens in the input string that are mappable to the output string. The computer system creates a set of initial mappings for a set of common tokens in the mappable tokens. The set of initial mappings maps the set of common tokens from the input string to the output string. The computer system creates a set of user mappings that maps the mappable tokens from input string to the output string using a user input to the set of initial mappings. The computer system generates program code that transform input strings to output strings using the set of user mappings that maps the mappable tokens from input string to the output string, wherein the program code is used to transform input strings to output strings.

Abstract: In an integrated circuit (IC) assessment method, an artificial intelligence (AI) component comprising at least one artificial neural network (ANN) is trained to transform layout rendering tiles of a rendering of a reference IC into corresponding reference layout image tiles extracted from at least one layout image of the reference IC. Using the trained AI component, standard cell layout renderings of a library of GDSII or OASIS standard cell layout renderings are transformed into as-fabricated standard cell layout renderings forming a library of as fabricated standard cell layout renderings. Instantiated standard cells and their placements in the layout image of an IC-under-test are identified by matching the instantiated standard cells with corresponding as-fabricated standard cell layout renderings retrieved from the library of as fabricated standard cell layout renderings.

Abstract: A display control device includes a first display control unit performing control so as to display a page, which is being displayed in a real space, in a first material as a presentation material used in a presentation by a presenter in a first position in a virtual reality space, a second display control unit performing control so as to display a second material in a second position which is different from the first position in the virtual reality space, and an operation input information acquisition unit acquiring first operation input information as operation input information which is input by a viewer experiencing the virtual reality space and which is about display of the second material, in which the second display control unit changes a display manner of the second material based on the first operation input information.

Abstract: A method and computing system for performing the method are presented. The method may include receiving image information representing an object; identifying a set of one or more matching object recognition templates associated with a set of one or more detection hypotheses. The method may further include selecting a primary detection hypothesis associated with a matching object recognition template; generating a primary candidate region based on the matching object recognition template; determining at least one of: (i) whether the set of one or more matching object recognition templates has a subset of one or more remaining matching templates, or (ii) whether the image information has a portion representing an unmatched region; and generating a safety volume list based on at least one of: (i) the unmatched region, or (ii) one or more additional candidate regions that are generated based on the subset of one or more remaining matching templates.

Abstract: In some aspects, systems and methods for efficiently clustering a large-scale dataset for improving the construction and training of machine-learning models, such as neural network models, are provided. A dataset used for training a neural network model configured can be clustered into a first set of clusters and a second set of clusters. The neural network model can be constructed with a number of nodes in a hidden layer that is based on the number of clusters in the first set of clusters. The neural network can be trained based on training samples selected from the second set of clusters. In some aspects, the trained neural network model can be utilized to satisfy risk assessment queries to compute output risk indicators for target entities. The output risk indicator can be used to control access to one or more interactive computing environments by the target entities.

Abstract: Video encoders and video decoders are configured to supplemental enhancement information (SEI) messages. The SEI messages may include picture orientation transform type syntax elements that indicate how a picture may be rotated and/or mirrored. The SEI messages may also include quality metrics.

Abstract: A method of machining a surface of a component. The method comprises scanning the surface of the component to obtain scanned electronic 3D data representing the scanned surface of the component locating a surface defect of the scanned surface and identifying a defect region that surrounds and includes the surface defect, and providing electronic 3D data representing a patch having the desired shape of the defect region. The method also comprises transforming the patch to generate a tooling path for repairing the surface defect. The transformation comprising translating a plurality of nodes of the patch. The translation distance of each node based on the distance of that node from an origin node of the patch. The method further comprises machining the surface of the component according to the generated tooling path.

Abstract: This application relates to a tissue nodule detection and tissue nodule detection model training method, apparatus, device, storage medium and system.

Abstract: Methods and systems for controlling navigation of an autonomous vehicle for traversing a drivable area are disclosed. The methods include receiving information relating to a drivable area that includes a plurality of polygons, identifying a plurality of logical edges that form a boundary of the drivable area, sequentially and repeatedly analyzing concavities of each the plurality of logical edges until identification of a first logical edge that has a concavity greater than a threshold, creating a first logical segment of the boundary of the drivable area. This segmentation may be repeated until each of the plurality of logical edges has been classified. The method may include creating and adding (to a map) a data representation of the drivable area that comprises an indication of the plurality of logical segments, and adding the data representation to a road network map comprising the drivable area.

Abstract: Techniques related to embedding a 3D object model within a 3D scene are discussed. Such techniques include determining two or more object mask images for two or more corresponding cameras trained on the 3D scene, projecting 3D points from the 3D object model to the image planes of the two or more cameras, and determining a position and orientation of the 3D object model in the scene using the object mask images and the projected 3D points.

Abstract: Systems and methods are provided for utilizing histogram views for improved visualization of three-dimensional (3D) medical images. Imaging data obtained during medical imaging examination of a patient may be processed, with the imaging data corresponding to a particular medical imaging technique. At least one medical image may be generated based on processing of the imaging data. Histogram data may be generated based on the at least one medical image. At least one histogram may be displayed along with the at least one medical image or a projection of the at least one medical image, with the at least one histogram including or being is based on the histogram data, and with the at least one histogram being displayed next to and aligned with the at least one medical image or the projection of the at least one medical image.

Abstract: Techniques for texture-based authentication of digital identity documents are disclosed. The disclosed techniques include authentication based on global texture information and/or on local texture information. Global texture-based authentication may include generating a global texture profile for an identity document image and comparing the global texture profile with a stored profile associated with a jurisdiction class of the identity document. Local texture-based authentication may include generating one or more local texture patches representative of texture information of one or more select local blocks of the ID. The one or more local texture patches are provided as input to one or more local detectors each trained to detect the presence of a forgery based on a target manipulation space.

Abstract: The image recognition method includes: obtaining an image data stream, wherein the image data frame includes a current frame; performing image recognition on an object in the current frame to generate a first box corresponding to the current frame; detecting movement of the object to generate a second box corresponding to the current frame; and determining the object as a tracking target according to the first box and the second box.

Abstract: A document processing apparatus includes a processor configured to extract an image area, in which an image is disposed, from a plurality of documents to be processed, perform an image recognition process on the image area, compare information on the image of the image area for each document, the information being obtained by performing the image recognition process, and decide a difference for the documents based on a result of comparison of the information on the image and a decision rule for the documents.

Abstract: A series of steps may be performed to automatically extract structured data from an image. First, anchor points may be extracted from the image, representing areas of the image that potentially contain information of interest. The arrangement of anchor points may be used to identify a template. A transform may be generated, to facilitate mapping between particular points in the selected template and corresponding points in the image. The transform may then be used to automatically read visual information from the image and extract structured data from the visual information.

Abstract: A computer-implemented tool for automated classification and interpretation of documents, such as life science documents supporting clinical trials, is configured to perform a combination of raw text, document construct, and image analyses to enhance classification accuracy by enabling a more comprehensive machine-based understanding of document content. The combination of analyses provides context for classification by leveraging relative spatial relationships among text and image elements, identifying characteristics and formatting of elements, and extracting additional metadata from the documents as compared to conventional automated classification tools.

Abstract: A method and encoding unit for encoding a block of pixels into a compressed data structure determines a set of Haar coefficients for a 2×2 quad of pixels of the block of pixels, which set includes a plurality of differential coefficients and an average coefficient. A first portion of the compressed data structure is determined using the differential coefficients and includes a first set of bits which indicates an order of the magnitudes of the differential coefficients, and a second set of bits which indicates a sign and an exponent for each of one or more of the differential coefficients which are non-zero. A second portion of the compressed data structure is determined using the average coefficient determined for the 2×2 quad of pixels. The compressed data structure is stored.

Abstract: Example systems, devices, media, and methods are described for controlling one or more virtual elements on a display in response to hand gestures detected by an eyewear device that is capturing frames of video data with its camera system. An image processing system detects a hand and presents a menu icon on the display in accordance with a detected current hand location. The image processing system detects a series of hand shapes in the captured frames of video data and determines whether the detected hand shapes match any of a plurality of predefined hand gestures stored in a hand gesture library. In response to a match, the method includes executing an action in accordance with the matching hand gesture. In response to an opening gesture, an element animation system presents one or more graphical elements incrementally moving along a path extending away from the menu icon. A closing hand gesture causes the elements to retreat along the path toward the menu icon.

Abstract: Wearable systems for privacy preserving expression generation for augmented or virtual reality client applications. An example method includes receiving, by an expression manager configured to communicate expression information to client applications, a request from a client application for access to the expression information. The expression information reflects information derived from one or more sensors of the wearable system, with the client application being configured to present virtual content including an avatar rendered based on the expression information. A user interface is output for presentation which requests user authorization for the client application to access the expression information. In response to receiving user input indicating user authorization, enabling access to the expression information is enabled. The client application obtains periodic updates to the expression information, and the avatar is rendered based on the periodic updates.

Abstract: Embodiments relate to a method for updating query information for tracing a target object from multi-camera including receiving a query information update command including query information for tracing a target object from multi-camera, searching for at least one image displaying the target object among a plurality of images captured by the multiple cameras, and updating the query information of a query image based on the at least one found image, and a multi-camera system performing the same.

Abstract: Aspects of the disclosure can provide a method, a corresponding target video processing package may be automatically obtained through matching according to scene description information, so that an operation of manually making a selection by a user in the related art is omitted. Therefore, matching efficiency of video processing manners may be improved. In addition, a plurality of video processing manners may be obtained through matching at a time, so that the matching efficiency is further improved. In addition, because the target video processing package is dynamically and correspondingly obtained through matching based on the scene description information, the target video processing package obtained through matching can be caused to accord with actual video content as much as possible. Further, accuracy of video processing may be improved, to satisfy an actual requirement of a user as much as possible.

Abstract: Systems and methods for automatically aggregating, evaluating, and providing a contextually relevant offer or incentive is disclosed. One method obtains a plurality of offers for a customer. Each of the plurality of offers is then evaluated to determine a contextual relevance of each of the plurality of offers. Each of the plurality of offers is then sorted into a best contextually relevant offer to a least contextually relevant offer order. The obtaining, evaluating, and sorting is continuously repeated until a time for using an offer is identified. The system and method then present the best contextually relevant offer.

Abstract: An ultrasound diagnostic apparatus includes: a hardware processor that search for a blood vessel position of a subject in a tomographic image and automatically setting a region corresponding to the blood vessel position detected in the tomographic image as a measurement region for generating a Doppler image. In a case where a measurement region has been already set or in a case where a specified position specified by a user exists when the hardware processor automatically sets the measurement region, the hardware processor executes processing of searching for the blood vessel position such that the measurement region is automatically set near the measurement region that has been already set or the specified position.

Abstract: An obstacle recognition assistance device includes: a memory configured to store instructions; and a processor configured to execute the instructions to acquire a first recognition result and sensing information. The first recognition result is a result based on a first recognition process performed using the sensing information acquired by an obstacle sensing device. The first recognition result indicates whether or not an obstacle is present. The processor is further configured to execute the instructions to verify whether the first recognition result is incorrect based on the first recognition result and a second recognition result. The second recognition result is a result based on a second recognition process performed using the sensing information. The second recognition process indicates whether or not the obstacle is present. The processor is further configured to execute the instructions to record a verification result.

Abstract: Disclosed is a computer-implemented method which encompasses registering a tracked imaging device such as a microscope having a known viewing direction and an atlas to a patient space so that a transformation can be established between the atlas space and the reference system for defining positions in images of an anatomical structure of the patient. Labels are associated with certain constituents of the images and are input into a learning algorithm such as a machine learning algorithm, for example a convolutional neural network, together with the medical images and an anatomical vector and for example also the atlas to train the learning algorithm for automatic segmentation of patient images generated with the tracked imaging device. The trained learning algorithm then allows for efficient segmentation and/or labelling of patient images without having to register the patient images to the atlas each time, thereby saving on computational effort.

Abstract: A synthetic aperture radar image analysis system 20 includes: a phase correlation determination means 21 which determines a strength of the phase correlation between a plurality of pixels in an image selected from among a plurality of images on the basis of the plurality of images that have been photographed by a synthetic aperture radar and show the same point; a shape determination means 22 which determines a degree of similarity between the shape of the distribution of the plurality of pixels and an object shape indicated by geospatial information; and an association means 23 which associates the plurality of pixels with the object on the basis of the determined strength of the phase correlation and the determined degree of similarity.

Abstract: Embodiments pertain to an imaging system configured to reduce or prevent the effect of unwanted specular reflections reflected by specular surfaces located in a scene. The system comprises at least one image acquisition device for acquiring a scene image comprising a specular surface providing specular light reflections. The at least one image acquisition device comprises at least one first image sensor and imaging optics having an optical axis for guiding light received from the scene along the optical axis onto the at least one first image sensor. The system further comprises at least one polarization filter operably positioned between the at least one first image sensor and an object. The system is configured to determine a polarization filter orientation such that an amount of specular light reflections incident onto the at least one first image sensor is reduced or eliminated.

Abstract: A system described herein may provide a technique for the use of machine learning techniques to perform authentication, such as biometrics-based user authentication. For example, user biometric information (e.g., facial features, fingerprints, voice, etc.) of a user may be used to train a machine learning model, in addition to a noise vector. A representation of the biometric information (e.g., an image file including a picture of the user's face, an encoded file with vectors or other representation of the user's fingerprint, a sound file including the user's voice, etc.) may be iteratively transformed until the transformed biometric information matches the noise vector, and the machine learning model may be trained based on the set of transformations that ultimately yield the noise vector, when given the biometric information.

Abstract: Techniques related to performing image registration are discussed. Such techniques include converting a source image region and a target image portion from a color image space to a semantic space and iteratively converging homography parameters using the source image region and target image portion in the semantic space by applying iterations with some homography parameters allowed to vary and others blocked from varying and subsequent iterations with all homography parameters allowed to vary.

Abstract: Techniques for enforcing trust policies for payload data transmitted through a data provisioning layer include: receiving, by a node in the data provisioning layer, payload data to be delivered to a recipient; obtaining, by the node, a trust policy indicating multiple attributes used to determine trustworthiness of payloads; determining, by the node, a set of values of the attributes associated with the payload data; generating, by the node, a trustworthiness opinion based at least on the trust policy and the set of values of the attributes; transmitting, by the node, the payload data and the trustworthiness opinion via the data provisioning layer toward the recipient; computing, by the recipient, a trustworthiness metric associated with the payload data based at least on the trustworthiness opinion; and determining, by the recipient, an action to take with respect to the payload data based at least on the trustworthiness metric.

Abstract: An automated method for assembling common commercial documents such as invoices, bills of lading and purchase orders placed in multipage files containing multiple documents without separators is described. The method is applicable in the presence of attachments and utilizes training data consisting of fields of interest and their locations in documents together with invariant fields frequently present in documents.

Abstract: An apparatus comprises a storage device configured to store a plurality of dictionary data for respectively detecting a plurality of different objects from an image; and at least one processor configured to function as: a detection unit configured to use partial dictionary data of the plurality of dictionary data to detect an object corresponding to the partial dictionary data, with respect to each frame of an image of a plurality of frames obtained by an image capturing device; and a switching unit configured to switch the dictionary data to be used by the detection unit in the plurality of frames, according to a result of the object detection by the detection unit.