Abstract: Techniques for meter text detection and recognition are described herein. In an example, an application receives a first image, depicting information displayed by the meter, from an imaging device. One or more qualities of the first image may be assessed, such as focus or lighting. A setting of the imaging device may be adjusted. The adjusting may be based at least in part on the assessed quality of the first image and one or more characteristics of an optical character recognition (OCR) algorithm. Accordingly, the settings of the image-capture device are tuned to the needs of the OCR algorithm. A second image may be captured, depicting information displayed by the meter, using the imaging device adjusted according to the adjusted setting. The OCR algorithm may be applied to the second image to obtain an alphanumeric value associated with the second image. The alphanumeric value is obtained from the OCR algorithm.

Abstract: The invention relates to a system for assessing a pulmonary image which allows for an improved assessment with respect to lung nodules detectability. The pulmonary image is smoothed for providing different pulmonary images (20, 21, 22) with different degrees of smoothing, wherein signal values and noise values, which are indicative of the lung vessel detectability and the noise in these images, are determined and used for determining an image quality being indicative of the usability of the pulmonary image to be assessed for detecting lung nodules. Since a pulmonary image shows lung vessels with many different vessel sizes and with many different image values, which cover the respective ranges of potential lung nodules generally very well, the image quality determination based on the different pulmonary images with different degrees of smoothing allows for a reliable assessment of the pulmonary image's usability for detecting lung nodules.

Abstract: A system, method, and/or computer storage medium encoded with a computer program are disclosed for providing an interactive virtual event session for respective pluralities of devices substantially in real-time. A data communication session is provided, to which a plurality of computing devices operated by participants of an event session connect. Respective audio-video feeds including content captured by respective cameras and microphones configured with the plurality of computing devices are received. Moreover, at least some of the content in at least two of the respective audio-video feeds is adjusted, including by executing editing processes. Furthermore, a virtual setting for the event session is provided to each of the plurality of computing devices, and modified to include at least the adjusted content. Changing views of the adjusted content and the virtual setting is provided to each of the plurality of computing devices, using artificial intelligence.

Abstract: A method of instance segmentation, comprising, defining a bounding box, depth mapping the bounding box, sorting the depth map, estimating stability due to noise of the sorted depth map, detecting low frequency jumps of the sorted depth map based on the estimated stability, detecting high frequency jumps of the sorted depth map, comparing the detected low frequency jumps and the detected high frequency jumps, detecting at least one of a largest object and a closest object based on the comparison and pixel masking the at least one of the largest object and the closest object.

Abstract: A method for predicting a pulmonary disease includes acquiring a three-dimensional computed tomography (CT) image from two-dimensional CT images, each of which captures a respective body position of a first patient, dividing the three-dimensional CT image into a plurality of regions to obtain region-based three-dimensional CT images configured to be used for fractal analysis, calculating a region-based fractal dimension value indicating a fractal complexity of a respective region-based three-dimensional CT image among the generated region-based three-dimensional computed tomography images, adding additional information to the region-based fractal dimension value to generate high-dimensional data, and generating status information of the first patient based on the complexity of the generated high-dimensional data.

Abstract: Methods, systems, and non-transitory computer readable storage media are disclosed for utilizing a plurality of neural networks in a multi-branch pipeline to generate image masks for digital images. Specifically, the disclosed system can classify a digital image as a portrait or a non-portrait image. Based on classifying a portrait image, the disclosed system can utilize separate neural networks to generate a first mask portion for a portion of the digital image including a defined boundary region and a second mask portion for a portion of the digital image including a blended boundary region. The disclosed system can generate the mask portion for the blended boundary region by utilizing a trimap generation neural network to automatically generate a trimap segmentation including the blended boundary region. The disclosed system can then merge the first mask portion and the second mask portion to generate an image mask for the digital image.

Abstract: Methods and systems for crowd level estimation are provided. The system includes a plurality of performance modeling modules (206), an input module (202) and a crowd estimation technique integration module. The plurality of performance modeling modules (206) performance model each of a plurality of crowd estimation techniques based on an accuracy thereof at different crowd levels and/or at different locations. The input module (202) receives an image of a crowd. The crowd estimation technique integration module (208) selects one or more of the plurality of crowd estimation techniques in response to the performance modeling of the one or more of the plurality of crowd estimation techniques and an estimated crowd level and/or an estimated location. The crowd estimation technique integration module (208) then estimates a crowd count of the crowd in the received image in accordance with the selected one or more of the plurality of crowd estimation techniques.

Abstract: According to one embodiment, a method for generating a plurality of candidate visualizations. The method may include receiving a scenario description. The method may also include collecting a plurality of expert data using a training system based on the received scenario description. The method may further include generating at least one predictive model based on the collected plurality of expert data in order to execute the at least one generated predictive model during an application of a plurality of genetic algorithms.

Abstract: An extracorporeal circulation apparatus has a blood reservoir temporarily storing blood and a presence information acquisition unit to detect presence or absence of blood at respective wall locations in a two-dimensional array. A control unit determines the position of a blood surface on the basis of consecutive elements in the array having detected blood along at least one of a first direction parallel to the blood surface and a second direction perpendicular to the blood surface.

Abstract: A method for decoding an image by a decoding apparatus according to the present invention comprises the steps of: deriving predicted samples by performing prediction on a current block; determining whether the current block is to be divided, on the basis of a size and a maximum transform size of the current block; when the current block is determined to be divided, dividing the current block into transform blocks; deriving transform coefficients of the transform blocks; deriving residual samples by performing an inverse transform procedure for the transform coefficients; and generating a reconstructed picture on the basis of the residual samples and the predicted samples, wherein, when the size of the current block is larger than the maximum transform size, the current block is determined to be divided.

Abstract: The method for determining property feature segmentation includes: receiving a region image for a region; determining parcel data for the region; determining a final segmentation output based on the region image and parcel data using a trained segmentation module; optionally generating training data; and training a segmentation module using the training data S500.

Abstract: The disclosure discloses a method for video frame interpolation. The method includes: obtaining a first visual semantic feature and first pixel information of a first frame, and obtaining a second visual semantic feature and second pixel information of a second frame; generating semantic optical flow information based on the first visual semantic feature and the second visual semantic feature; generating pixel optical flow information based on the first pixel information and the second pixel information; and generating an interpolation frame between the first frame and the second frame based on the semantic optical flow information and the pixel optical flow information, and interpolating the interpolation frame between the first frame and the second frame.

Abstract: An apparatus for extracting a color scheme from a video is provided. The apparatus comprises: a semi-master shot segmentation part for segmenting an input video into a plurality of semi-master shots through semi-master-shot boundary detection (SBD); a base palette extraction part for extracting base palettes from the segmented semi-master shots; and a color scheme merging part for merging the base palettes extracted from the semi-master shots to extract a color scheme.

Abstract: The present invention discloses a system for precise representation of object segmentation with multi-modal input for real-time video applications. The multi-modal segmentation system takes advantage of optical, temporal as well as spatial information to enhance the segmentation for AR and VR or other entrainment purpose with accurate details. The system can segment foreground objects such as human and salient objects within a video frame and allows locating object-of-interest for multiple-purposes.

Abstract: Systems, devices, methods, and computer processing products for automatically checking for errors in segmentation (contouring) using heuristic and/or statistical evaluation methods.

Abstract: A determination apparatus generates an interval vector having a plurality of components that are adjacent occurrence intervals between a plurality of events that have occurred in chronological order. The determination apparatus generates a plurality of local variable points each of which includes specific components as one set of coordinates, using a predetermined number of consecutive interval vectors in the chronological order. The determination apparatus generates a Betti sequence by applying persistent homology transform to the plurality of local variable points for which the interval vectors serving as starting points are different. The determination apparatus determines a type of the plurality of events based on the Betti sequence.

Abstract: A server and a control method thereof are provided. The server includes a communicator configured to communicate with an external apparatus; and a processor configured to: receive an image from the external apparatus via the communicator, process the received image by applying a plurality of image analysis models of which an analysis type for the image is different from each other, to the received image, and generate analysis result information about the image respectively corresponding to a plurality of analysis types according to the processing of the received image. With this, more various types of image analysis information may be provided with respect to one image. At least a portion of the analysis of the image, the processing and the generation may be carried out using at least one of a machine learning, a nerve network or a deep learning algorithm as a rule based or artificial intelligence algorithm.

Abstract: The present application provides for systems and methods for detecting and estimating signals corresponding to one or more biomarkers in biological samples stained for the presence of protein and/or nucleic acid biomarkers. On particular aspect is directed to a method of estimating an amount of signal corresponding to at least one biomarker in an image of a biological sample. The method includes detecting isolated spots in a first image, deriving an optical density value of a representative isolated spot based on signal features from the detected isolated spots, estimating a number of predictive spots in signal aggregates in each of a plurality of sub-regions based on the derived optical density value of the representative isolated spot, and storing the estimated number of predictive spots and detected isolated spots in each of the plurality of generated sub-regions in a database.

Abstract: An endoscope system includes: a processor that generates first and second feature amount distribution images of a living tissue from an imaged image of the living tissue and generates a second feature amount distribution processed image from these distribution images; and a display that displays the second feature amount distribution processed image. The processor generates a mask image of the second feature amount distribution image by, in the first feature amount distribution image, setting a pixel whose pixel value representing the first feature amount is less than a lower limit value as a non-transmissive pixel having a transmittance of zero and setting a pixel between an upper limit value and the lower limit value as a transmissive pixel while giving the pixel a transmittance determined continuously or stepwise in accordance with the pixel value in the first feature amount distribution image.

Abstract: In one embodiment, a method includes receiving, by a device, playback content. The playback content is associated with an ATSC signal. The method also includes identifying, by the device, one or more markers in the playback content, communicating, by the device, information associated with the one or more markers to an advertisement decision engine, and receiving, by the device, a URL for an addressable targeted programmatic advertisement from the advertisement decision engine. The method further includes inserting, by the device, the addressable targeted programmatic advertisement URL into the playback content.

Abstract: Systems and methods are describe herein for managing a transaction between two parties. A distributed ledger management service (DLMS) microservice receives an electronic document pertaining to a transaction from a user. The electronic document includes transactional data. A document type is determined by the DLMS microservice. A portion of the transactional data is extracted from the electronic document based on the document type. The portion of the transactional data is provided to a distributed ledger node for decentralized storage and further reporting to a third party.

Abstract: Data gathered from a continual data source is converted into an image and represented by a rectilinear grid defining a grid of pixels. Each pixel in each axis unit of one axis is examined in parallel using a graphic processor unit (GPU) to determine whether any pixels exceed a predefined threshold. Those pixels that exceed the threshold are identified as positive return pixels. Within each axis unit groups of positive return pixels are identified based on a first axis epsilon. Adjacent groups of positive return pixels are assembled by merging the axis units based on a second axis epsilon. Groups of positive return pixels grouped together according to the first axis epsilon and the second axis epsilon are classified and reported as a signal.

Abstract: Aspects of the present invention disclose a method for automatic delineation and extraction of tabular data in portable document format (PDF). The method includes one or more processors extracting metadata corresponding to tabular data in a text-based portable document format (PDF), wherein the metadata is associated with characters and border lines of the tabular data. The method further includes generating a graph structure corresponding to the tabular data in the text-based PDF based at least in part on the metadata. The method further includes generating a vector representation of the graph structure. The method further includes constructing a tree structure corresponding to the tabular data based at least in part on the vector representation.

Abstract: The present invention relates to a method and system that automatically finds, segments and measures lesions in medical images following the Response Evaluation Criteria In Solid Tumours (RECIST) protocol. More particularly, the present invention produces an augmented version of an input computed tomography (CT) scan with an added image mask for the segmentations, 3D volumetric masks and models, measurements in 2D and 3D and statistical change analyses across scans taken at different time points. According to a first aspect, there is provided a method for determining volumetric properties of one or more lesions in medical images comprising the following steps: receiving image data; determining one or more locations of one or more lesions in the image data; creating an image segmentation (i.e. mask or contour) comprising the determined one or more locations of the one or more lesions in the image data and using the image segmentation to determine a volumetric property of the lesion.

Abstract: A system includes first and second sensors and a controller. The first sensor is of a first type and is configured to sense objects around a vehicle and to capture first data about the objects in a frame. The second sensor is of a second type and is configured to sense the objects around the vehicle and to capture second data about the objects in the frame. The controller is configured to down-sample the first and second data to generate down-sampled first and second data having a lower resolution than the first and second data. The controller is configured to identify a first set of the objects by processing the down-sampled first and second data having the lower resolution. The controller is configured to identify a second set of the objects by selectively processing the first and second data from the frame.

Abstract: A method for building a map includes: acquiring an original grayscale map, preprocessing the original grayscale map to obtain a preprocessed map, binarizing the preprocessed map to obtain a binarized map, performing a boundary filling to the preprocessed map and the binarized map to obtain a boundary-filled preprocessed map and a boundary-filled binarized map, performing a boundary thinning to the boundary-filled binarized map to obtain a thinned binarized map, and performing a boundary thinning to the boundary-filled preprocessed map, according to the thinned binarized map, to obtain a thinned preprocessed map.

Abstract: An imaging system and a method of imaging are provided. The imaging system includes a single optics module configured for focusing light reflected or emanated from a dynamic scene in the infrared spectrum and a synchronous focal plane array for receiving the focused light and acquiring infrared images having a high spatial resolution and a low temporal resolution from the received focused light. The imaging system further includes an asynchronous neuromorphic vision system configured for receiving the focused light and acquiring neuromorphic event data having a high temporal resolution, and a read-out integrated circuit (ROIC) configured to readout both the infrared images and event data.

Abstract: Efficient location and identification of documents in images. In an embodiment, at least one quadrangle is extracted from an image based on line(s) extracted from the image. Parameter(s) are determined from the quadrangle(s), and keypoints are extracted from the image based on the parameter(s). Input descriptors are calculated for the keypoints and used to match the keypoints to reference keypoints, to identify classification candidate(s) that represent a template image of a type of document. The type of document and distortion parameter(s) are determined based on the classification candidate(s).

Abstract: Aspects of the subject disclosure may include, for example, a method performed by a processing system of determining a present orientation of a display region presented at a first time on a display of a video viewer, predicting a future orientation of the display region occurring at a second time based on data collected, to obtain a predicted orientation of the display region to be presented at the second time on the display of the video viewer, identifying, based on the predicted orientation of the display region, a first group of tiles from a video frame of a panoramic video being displayed by the video viewer, wherein the first group of tiles covers the display region in the video frame at the predicted orientation, and a plurality of objects moving in the video frame from the first time to the second time, wherein each object of the plurality of objects is located in a separate spatial region of the video frame at the second time, wherein a second group of tiles collectively covers the separate spatial re

Abstract: The present disclosure involves systems, software, and computer implemented methods for transaction auditing. One example method includes training at least one machine learning model to determine features that can be used to determine whether an image is an authentic image of a document or an automatically generated document image, using a training set of authentic images and a training set of automatically generated document images. A request to classify an image as either an authentic image of a document or an automatically generated document image is received. The machine learning model(s) are used to classify the image as either an authentic image of a document or an automatically generated document image, based on features included in the image that are identified by the machine learning model(s). A classification of the image is provided. The machine learning model(s) are updated based on the image and the classification of the image.

Abstract: An example system includes a processor to receive an input and a model trained to classify inputs. The processor is to iteratively generate a perturbed input that optimizes a saliency metric including a classification term, a sparsity term, and a smoothness term, while keeping parameters of the model constant. The processor is to also detect that a predefined number of iterations is exceeded or a convergence of values of the perturbed input. The processor is to further generate a saliency mask based on a perturbation of the perturbed input in response to detecting the predefined number of iterations is exceeded or the convergence.

Abstract: The action schedule item creation ECU creates action schedule items demanded of an ego vehicle capable of switching between autonomous driving and manual driving. The HUD and the meter display are provided inside a cabin of the ego vehicle. The display control ECU displays the action schedule items created by the action schedule item creation ECU on the HUD and the meter display, and emphasizes display of action schedule items to be performed by manual driving compared to display of action schedule items to be performed by autonomous driving.

Abstract: Technologies pertaining to electronic document understanding are described herein. A document is received, wherein the document includes a section of a type. An image of the document is generated, and a candidate region is identified in the image of the document, wherein the candidate region encompasses the section. A label is assigned to the candidate region based upon text of the section, wherein the label identifies the type of the section. An electronic document understanding task is performed based upon the label assigned to the candidate region.

Abstract: The present invention discloses system and method for replacing a texture of a background region in a multimedia. The system is an AI-based multi-media processing system for replacing the original texture of the background of the multimedia with a texture template. The system applies a foreground mask to hide and protect the foreground region and multiple textures of the background. The system uses deep learning to segment specific texture from images or video sequences. The system replaces the texture of the original input image with a texture template to form a processed image.

Abstract: Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) are commonly used to assess patients with known or suspected pathologies of the lungs and liver. In particular, identification and quantification of possibly malignant regions identified in these high-resolution images is essential for accurate and timely diagnosis. However, careful quantitative assessment of lung and liver lesions is tedious and time consuming. This disclosure describes an automated end-to-end pipeline for accurate lesion detection and segmentation.

Abstract: A simulator environment is disclosed. In embodiments, the simulator environment includes graphics generation (GG) processors in communication with one or more display devices. Deep learning neural networks running on the GG processors are configured for run-time generation of photorealistic, geotypical content for display. The DL networks are trained on, and use as input, a combination of image-based input (e.g., imagery relevant to a particular geographical area) and a selection of geo-specific data sources that illustrate specific characteristics of the geographical area. Output images generated by the DL networks include additional data channels corresponding to these geo-specific data characteristics, so the generated images include geotypical representations of land use, elevation, vegetation, and other such characteristics.

Abstract: A method is for determining a processing sequence for processing an image, the processing sequence including a plurality of algorithms, each respective algorithm of the plurality of algorithms being configured to perform an image processing process on the image to generate a respective output. In an embodiment, the method includes determining one or more required outputs from the processing sequence; and determining, using a data processing system, the processing sequence based on the one or more required outputs determined, the data processing system being configured based on sequences previously determined.

Abstract: A method of adaptively updating an enrollment database is disclosed. The method may include extracting a first feature vector from an input image, the input image including a face of a user, determining whether to enroll the input image in the enrollment database based on the first feature vector, second feature vectors of enrollment images and a representative vector, the second feature vectors of the enrollment images being enrolled in the enrollment database, and the representative vector representing the second feature vectors, and enrolling the input image in the enrollment database based on a result of the determining.

Abstract: In an embodiment, an electronic processing system includes an image-processing circuit, a product-arrangement circuit, and a score circuit. The image-processing circuit is configured to receive an image of products disposed in a display structure having sections, to identify the sections, and to identify at least one respective product within each identified section. The product-arrangement circuit is configured to determine an arrangement of the identified products within the identified sections of the display structure, and to compare the determined arrangement to a product-arrangement template. And the score circuit is configured to generate a product-arrangement score in response to the comparing of the determined arrangement to the product-arrangement template.

Abstract: A computer-implemented method for determining field boundaries and crop forecasts in each field is provided. The method includes deriving vegetation indices for each geo-spatial pixel of each image of multi-spectral imagery at a plurality of points in time, constructing minimum bounding boxes for each image according to the vegetation indices, and generating, based on a neural network analysis of each image and the minimum bounding boxes, a geo-spatial plot of crops including a predicted plot of future crop usage for an area including each field in the multi-spectral imagery.

Abstract: An image processing device includes a document image extraction unit, a business card array image detection unit, and a business card image separation unit. The document image extraction unit extracts one document image in a read image obtained by scanning one or a plurality of documents placed on a platen glass of an image reading device. When the document is a plurality of business cards arranged without gaps, the business card array image detection unit detects the document image as a business card array image in which a plurality of business card images are arranged without gaps, based on at least one of the distribution of character string objects and the distribution of character sizes in the document image. The business card image separation unit separates the detected business card array image into the plurality of business card images.

Abstract: A control system for controlling an operation of an elevator arranged to service different floors of a building, is disclosed. The control system comprises an input interface configured to receive a measurement of a distance metric to an object located at a service floor in a line-of-sight of a sensor; an output interface configured to cause a display device to display a floor value indicating a destination floor; and a processor configured to compare the received distance metric with a referenced distance metric to estimate a sign of the comparison and a value of the comparison; repeatedly update, until a termination condition is met, the floor value displayed on the display device in a direction of the elevator service indicated by the sign and with a frequency of the update indicated by the value; and cause the elevator to perform the service operation from the service floor to the destination floor.

Abstract: Systems and methods for identifying and assessing lymph nodes are provided. Medical image data (e.g., one or more computed tomography images) of a patient is received and anatomical landmarks in the medical image data are detected. Anatomical objects are segmented from the medical image data based on the one or more detected anatomical landmarks. Lymph nodes are identified in the medical image data based on the one or more detected anatomical landmarks and the one or more segmented anatomical objects. The identified lymph nodes may be assessed by segmenting the identified lymph nodes from the medical image data and quantifying the segmented lymph nodes. The identified lymph nodes and/or the assessment of the identified lymph nodes are output.

Abstract: Methods, devices, and systems related to a user interface for modifying pictures are described. Modifying pictures can include placing an image of a picture in a different picture, replacing an image of the picture with a different image, deleting an image from the picture, and/or storing an image from the picture. In an example, a method can include displaying a first picture on a user interface of a mobile device, receiving, on the user interface, a selection of at least one foreground image included in the first picture, receiving, on the user interface, a selection of a background image included in a library of images, and displaying, on a user interface, a second picture including the at least one selected foreground image and the selected background image responsive to receiving the selection of the at least one foreground image followed by the selection of the background image.

Abstract: A variety of applications exploiting the Shapeless language where the geometry of letters is immaterial; their size and proximity deliver their message. These applications span rescue effort, industrial practice, painting, food preparation, authentication of documents, etc. Shapeless language is computer readable and very robust.

Abstract: Systems and methods for self-supervised learning for visual odometry using camera images captured on a camera, may include: using a key point network to learn a keypoint matrix for a target image and a context image captured by the camera; using the learned descriptors to estimate correspondences between the target image and the context image; based on the keypoint correspondences, lifting a set of 2D keypoints to 3D, using a learned neural camera model; estimating a transformation between the target image and the context image using 3D-2D keypoint correspondences; and projecting the 3D keypoints into the context image using the learned neural camera model.

Abstract: An image processing method, an image processing apparatus, an electronic device and a computer readable storage medium are provided. The image processing method includes the following. A background image and a portrait region image of a current user that a preset parameter of the background image matching the preset parameter of the portrait region image are acquired. The portrait region image and the background image are merged to obtain a merged image.

Abstract: An actuator to execute on a server may be automatically selected based on risk of failure and damage to the server. Requirement specification and environment parameters may be received. A subset of actuators may be selected based on a risk threshold from an actuator catalog database storing actuator information and actuator risk metadata associated with a plurality of actuators. The actuator risk metadata may be augmented with risk information. A ranked list of the subset of actuators may be generated based on the actuator risk metadata associated with each actuator in the subset. An actuator in the ranked list may be executed on the server.

Abstract: An image processing circuit is provided. The image processing circuit includes a dither computing circuit and a blending circuit. The dither computing circuit performs a dither computing on the input grayscale data to generate a dithered grayscale data. The blending circuit receives the input grayscale data and the dithered grayscale data, generates a blending weight by comparing the input grayscale data with a first threshold, and performs a blending computing on the input grayscale data and the dithered grayscale data based on the blending weight to output an output grayscale data.

Abstract: An image sensor comprises a pixel array having a plurality of pixels arranged in a matrix, a readout unit that controls readout of signals from the plurality of pixels, an output unit that outputs the read signals as an image signal and an extraction unit that performs feature amount extraction processing to extract a feature amount using the read signals. The readout of the signals by the readout unit and the feature amount extraction processing by the extraction unit are processed in parallel.