Abstract: Methods and systems for displaying images of cells in a sample include obtaining a plurality of images of cells in the sample, where each image corresponds to one of the cells in the sample, determining values of at least one property for each of the cells based on the plurality of images, arranging the plurality of images to form a first image array, where the images are ordered in the first image array based on the values of the at least one property, displaying the first image array, sorting the plurality of images to form a second image array in which an ordering of the images is different from the first image array, and displaying the second image array, where the sample includes blood and the cells include red blood cells.

Abstract: Described herein are methods for identifying quasispecies of genomes by clustering sequence reads for samples including the genomes based on the similarities of the sequence reads.

Abstract: A group to be authenticated in face authentication is efficiently registered in a system. An information processing system includes a face detection unit configured to detect a face from an image in which a plurality of faces of persons are shown, a determination unit configured to determine whether or not the face detected by the face detection unit satisfies a predetermined condition, and a registration information generation unit configured to generate registration information, the registration information being information in which a partial image of each of a plurality of faces that have been determined to satisfy the predetermined condition is associated with an identifier identifying a group to be authenticated in face authentication.

Abstract: The technology disclosed relates to generating ground truth training data to train a neural network-based template generator for cluster metadata determination task. In particular, it relates to accessing sequencing images, obtaining, from a base caller, a base call classifying each subpixel in the sequencing images as one of four bases (A, C, T, and G), generating a cluster map that identifies clusters as disjointed regions of contiguous subpixels which share a substantially matching base call sequence, determining cluster metadata based on the disjointed regions in the cluster map, and using the cluster metadata to generate the ground truth training data for training the neural network-based template generator for the cluster metadata determination task.

Abstract: An image positioning device is provided in the invention. The image positioning device includes a calculation circuit and a positioning circuit. The calculation circuit obtains a plurality of images from an image capturing device and classifies the images into a plurality of main groups based on a first algorithm, wherein each main group corresponds to a different area and the calculation circuit classifies the images of each main group into a plurality of sub-groups based on a feature of each image of each main group and a clustering algorithm. The positioning circuit is coupled to the calculation circuit. The positioning circuit positions each sub-group in the area corresponding to each main group based on the relative position relationship between each sub-group of each main group.

Abstract: An assignment control apparatus includes an assignment device connected to multiple cameras and multiple specialized devices connected to the assignment device and each corresponding to one of preset multiple categories. The assignment device includes multiple determination units connected to the cameras one-to-one and each configured to determine the category of image data received from the camera to which the determination unit is connected, the category being one of the categories, and to output the image data along with category data indicating the determined category. The assignment device also includes an assignment unit configured to output the image data outputted from each specialized device to the specialized device corresponding to the category indicated by the category data outputted along with the image data.

Abstract: In an example implementation according to aspects of the present disclosure, a system, method, and storage medium for processing digital image file metadata characteristics. The system includes a processor and memory. The processor executes machine readable instructions to receive a set of digital image files from a first client application. The processor extracts a set of metadata from the set of digital image files. The processor identifies a set of common characteristics within the set of metadata. The processor groups the set of digital image files based on the set of common characteristics. The processor evaluates an association between the set of common characteristics and a second user. Responsive to the evaluation, the processor sends the grouped set of digital image files to a second client application.

Abstract: Provided are a video data acquisition unit that acquires video data; a parking detection unit that detects whether the vehicle is parked; a moving body detection unit that detects a moving body from video data while the vehicle is parked; an acceleration detection unit that detects acceleration applied to the vehicle; a parking position determination unit that determines whether the vehicle is parked at a location where people or vehicles often pass close to the vehicle, based on position information of the vehicle; and a recording function control unit that selectively performs a process of storing video data based on detection of a moving body by the moving body detection unit, and a process of storing video data based on acceleration detected by the acceleration detection unit, according to a determination result of the parking position determination unit.

Abstract: Provided are an image processing device, an image processing method, and an image processing program that can decide a user image that is similar to a plurality of model images and that follows a flow of the plurality of model images. Combinations of (I2) and (P3), (I51) and (P21), (I150) and (P49), (I198) and (P79), (I201) and (P30), (I249) and (P99), (I300) and (P101), and (I301) and (P112) in which similarities between the model images and the user images are equal to or more than a first threshold value are detected. The combination of (I201) and (P30) in which a relative time difference of the imaging time is equal to or more than a second threshold value is eliminated, and the rest combinations are second combinations. From among the second combinations, a model image group and a user image group, which are a collection of similar images, are decided, and the user images similar to the model images attached on a model album are decided from the user image group.

Abstract: The system and method are directed to a prototypical contrastive learning (PCL). The PCL explicitly encodes the hierarchical semantic structure of the dataset into the learned embedding space and prevents the network from exploiting low-level cues for solving the unsupervised learning task. The PCL includes prototypes as the latent variables to help find the maximum-likelihood estimation of the network parameters in an expectation-maximization framework. The PCL iteratively performs an E-step for finding prototypes with clustering and M-step for optimizing the network on a contrastive loss.

Abstract: Approaches to zero-shot learning include partitioning training data into first and second sets according to classes assigned to the training data, training a prediction module based on the first set to predict a cluster center based on a class label, training a correction module based on the second set and each of the class labels in the first set to generate a correction to a cluster center predicted by the prediction module, presenting a new class label for a new class to the prediction module to predict a new cluster center, presenting the new class label, the predicted new cluster center, and each of the class labels in the first set to the correction module to generate a correction for the predicted new cluster center, augmenting a classifier based on the corrected cluster center for the new class, and classifying input data into the new class using the classifier.

Abstract: Provided are an electronic device and an operation method thereof. The electronic device includes a memory that stores one or more instructions, and a processor that executes the one or more instructions stored in the memory, wherein the processor is configured to execute the one or more instructions to: divide original image data into a plurality of image sequences; determine a predetermined number of image sequences among the plurality of image sequences as an input image group, select one of the image sequences included in the input image group and add the selected image sequence to the highlight image group based on one or more image sequences pre-classified as a highlight image group, by using a trained model trained using an artificial intelligence algorithm; and generate summary image data extracted from the original image data, by using the image sequence included in the highlight image group.

Abstract: One or more embodiments of the disclosure include a character management system that determines and utilizes contextual meaning with regard to standardized image characters. In particular, the character management system determines contextual meaning with regard to standardized characters based on the manner in which the standardized characters are utilized in a repository of electronic documents. Moreover, the character management system can utilize the contextual meaning to search, recommend, analyze, and translate with regard to the use of standardized image characters.

Abstract: The method for classifying ambiguous objects, including: determining initial labels for an image set; determining N training sets from the initially-labelled image set; training M annotation models using the N training sets; determining secondary labels for each image of the image set using the M trained annotation models; and determining final labels for the image set based on the secondary labels. The method can optionally include training a runtime model using images from the image set labeled with the final labels; and optionally using the runtime model.

Abstract: A method for automated routing of pictures taken on mobile electronic devices to a digital picture frame including a camera integrated with the frame, and a network connection module allowing the frame for direct contact and upload of photos from electronic devices or from photo collections of community members. The integrated camera is used to automatically determine an identity of a frame viewer and can capture gesture-based feedback. The displayed photos are automatically shown and/or changed according to the detected viewers. The photos can be filtered and cropped at the receiver side. Clustering photos by content is used to improve display and to respond to photo viewer desires.

Abstract: Systems and methods are provided for generating training data for a machine-learning classifier. A knowledge representation synthesized based on an object of interest is used to assign labels to content items. The labeled content items can be used as training data for training a machine learning classifier. The labeled content items can also be used as validation data for the classifier.

Abstract: Methods and systems for determining relevance for a new document are described. Existing documents that have a high probability of relevance can be chosen. A vocabulary of words in the existing documents can be built. Each word can be mapped into a vector such that each existing document can be represented by a sequence of vectors and each sentence and/or paragraph in each existing document can be represented by a subsequence of vectors including a subset of the sequence of vectors. Data augmentation can be applied changing an order of the subsequences in order to create additional documents represented by the subsequences. A deep neural network can be trained using the subsequences that represent the existing documents and the subsequences that represent additional documents. The new documents can be trained using a trained deep neural network. A relevant document can be output using the trained deep neural network.

Abstract: A system and method for sequence extraction using screenshot images to generate a robotic process automation workflow is disclosed. The system and method include capturing a plurality of screenshots of steps performed by a user on an application using a processor, storing the screenshots in memory, determining action clusters from the captured screenshots by randomly clustering actions into an arbitrary predefined number of clusters, wherein screenshots of different variations of a same action is labeled in the clusters, extracting a sequence from the clusters, and discarding consequent events on the screen from the clusters, and generating an automated workflow based on the extracted sequences.

Abstract: An image display method applicable to a video conferencing system with a wide-angle webcam is disclosed. The wide-angle webcam is used to capture a panoramic image having an aspect ratio greater than or equal to 2:1. The method includes: framing multiple regions of interest (ROIs) according to the panoramic image, each ROI having at least one of attributes; selecting one from predetermined frame layouts as an output frame layout according to whether to insert a portion of the panoramic image and attributes, positions and the number of the ROIs; and inserting at least one of the portion of the panoramic image and the ROIs into corresponding windows in the output frame layout to form a composite frame according to the attributes of the ROIs.

Abstract: An apparatus that assists an survey of a crop cultivated in each of blocks obtained by dividing a field, comprising: an input unit configured to accept, for an survey executed for the crop, the input of identification information identifying at least one of the surveys, block information indicating the block where the survey has been executed, item information indicating an survey item, and measured values measured at survey positions; and a processing unit configured to cause a transition in the aggregating result to be displayed as a result of the survey, wherein the input unit further accepts the input of a user operation specifying part of the transition of a result of aggregating the input measured values; and of the measured values, the processing unit causes reliability information of the aggregating result of the part to be displayed.

Abstract: Provided is a method of DNN-based image processing by an imaging device. The method comprises obtaining, by the imaging device, at least one input image with a plurality of color channels, simultaneously extracting, by the imaging device, a semantic information from each of the color channels of the at least one input image and a color correlation information from each of the color channels of the at least one input image, and generating, by the imaging device, at least one output image based on the extracted semantic information and the extracted color correlation information.

Abstract: A group to be authenticated in face authentication is efficiently registered in a system. An information processing system includes a face detection unit configured to detect a face from an image in which a plurality of faces of persons are shown, a determination unit configured to determine whether or not the face detected by the face detection unit satisfies a predetermined condition, and a registration information generation unit configured to generate registration information, the registration information being information in which a partial image of each of a plurality of faces that have been determined to satisfy the predetermined condition is associated with an identifier identifying a group to be authenticated in face authentication.

Abstract: Dense feature scale detection can be implemented using multiple convolutional neural networks trained on scale data to more accurately and efficiently match pixels between images. An input image can be used to generate multiple scaled images. The multiple scaled images are input into a feature net, which outputs feature data for the multiple scaled images. An attention net is used to generate an attention map from the input image. The attention map assigns emphasis as a soft distribution to different scales based on texture analysis. The feature data and the attention data can be combined through a multiplication process and then summed to generate dense features for comparison.

Abstract: A method of creating an album. The method includes a setting step of setting a first condition for generating a first page included in a first album and a second condition for generating a second page included in a second album, and a creation step of creating the first album including the first page generated in accordance with the first condition and a common page common to the first album and the second album and creating the second album including the second page generated in accordance with the second condition and the common page. At the creation step, by performing control to make the same a total number of pages of the first album and a total number of pages of the second album, the first album and the second album having the same total number of pages are created.

Abstract: Techniques are described that exclude use of “stop-fingerprints” from media database formation and search query to an automatic content recognition (ACR) systems based on media content fingerprints updated by stop-fingerprint analysis. A classification process is presented which takes in fingerprints from reference media files as an input and produces a modified set of fingerprints as an output by applying a novel stop-fingerprint classification algorithm. Architecture for the distributed stop-fingerprint generation is presented. Various cases, as stop-fingerprints generation for the entire reference database, stop-fingerprints generation for the individual reference fingerprint files, and temporal fingerprint classification obtained through intermediate steps of the temporal fingerprint classification algorithm are presented. A hash-based signature classification algorithm is also described.

Abstract: The present disclosure provides systems and methods that use and/or generate image files according to a novel microvideo image format. For example, a microvideo can be a file that contains both a still image and a brief video. The microvideo can include multiple tracks, such as, for example, a separate video track, audio track, and/or one or more metadata tracks. As one example track, the microvideo can include a motion data track that stores motion data that can be used (e.g., at file runtime) to stabilize the video frames. A microvideo generation system included in an image capture device can determine a trimming of the video on-the-fly as the image capture device captures the microvideo.

Abstract: Dynamically changing a content based on a user-defined context includes receiving, by one or more processors, input data from a user, the input data includes at least one document with an annotated part identifying a first content element, the first content element is associated with a first content type. The one or more processors determine a context information associated with the annotated part and extract the annotated part. A first replacement for the first content element is retrieved from a first data source selected based on the content information. The one or more processors replace the first content element in the at least one document with the first replacement.

Abstract: A method, computer program product and computer system to generate a spatial visualization of topics contained in messages data is provided. A processor retrieves message data associated with a user. A processor determines one or more topics represented by the message data. A processor generates a spatial visualization of one or more user interface elements, where the spatial visualization includes a size and a location for the one or more user interface elements. A processor displays one or more user interface elements corresponding to the one or more topics.

Abstract: A method, computer program product and computer system to generate a spatial visualization of topics contained in messages data is provided. A processor retrieves message data associated with a user. A processor determines one or more topics represented by the message data. A processor generates a spatial visualization of one or more user interface elements, where the spatial visualization includes a size and a location for the one or more user interface elements. A processor displays one or more user interface elements corresponding to the one or more topics.

Abstract: [Object] There is provided a mechanism that makes it possible to efficiently specify an important region of a moving image including a dynamic content. [Solution] An information processor including a control unit that recognizes a motion of an operator with respect to an operation target in a moving image and specifies an important region of the operation target in the moving image on a basis of an operation position of the operator.

Abstract: A computer implemented method of document classification includes receiving a text document. A first classification is generated for the document, and a text corpus is searched for one or more terms from the document. Searched terms having an incidence in the text corpus lower than a threshold incidence are flagged, and at least one classification is generated after removing at least one flagged term from the document. An output is generated if the further classification is different from the first classification.

Abstract: Described is a system for online vehicle recognition in an autonomous driving environment. Using a learning network comprising an unsupervised learning component and a supervised learning component, images of moving vehicles extracted from videos captured in the autonomous driving environment are learned and classified. Vehicle feature data is extracted from input moving vehicle images. The extracted vehicle feature data is clustered into different vehicle classes using the unsupervised learning component. Vehicle class labels for the different vehicle classes are generated using the supervised learning component. Based on a vehicle class label for a moving vehicle in the autonomous driving environment, the system selects an action to be performed by the autonomous vehicle, and causes the selected action to be performed by the autonomous vehicle in the autonomous driving environment.

Abstract: An object is to provide a technique capable of reducing an inter-SoC communication volume. The screen generation device includes a first SoC, a second SoC, and an allocation unit. The allocation unit defines a plurality of superposition sequence layers having a superposition sequence and selected from the plurality of first drawing layers and the plurality of second drawing layers, allocates, among the plurality of superposition sequence layers, a consecutive superposition sequence layer cluster being consecutive two or more superposition sequence layers in the superposition sequence, to the first SoC, and allocates remaining superposition sequence layers being one or more superposition sequence layers other than the consecutive superposition sequence layer cluster to the second SoC.

Abstract: Technologies are provided for determining deficiencies in narrative textual data that may impact decision-making in a decisional context. A candidate text document and a reference corpus of text may be utilized to generate one or more topic models and document-term matrices, and then to determine a corresponding statistical perplexity and probabilistic coherence. The reference corpus may be known or normatively deemed to be epistemically persuasive and adequate with respect to a particular context. Statistical determinations of a degree to which the candidate deviates from the reference normative corpus are determined, in terms of the statistical perplexity and probabilistic coherence of the candidate as compared to the reference.

Abstract: A proactive operations (ProOps) platform is contemplated to facilitate processing data for purposes of turning included information into action, such as to enable operators to proactively manage network operations using information derived from mathematical analysis of raw data collected from network devices.

Abstract: A method and system for analyzing data based on a statistical model, wherein the statistical model is used in one or more contexts without needing intervention of data scientists. This statistical model is parameterized and uploaded in an analytics platform. Parameterizing the statistical model enables end users to select scope, constraints and variables of data analysis. Acceptance indicator of this tool indicates reliability of the model on user selected scope, constraints and variables. Based on user selections, a dynamic table is created which is an input to the statistical model for data analysis. Based on values of this dynamic table, data analysis is performed on stored data on the specific context. The report id generated based on the data analysis which is presented to user as visual output.

Abstract: Techniques are disclosed for detecting the bounds of borderless open tables in fixed-format structured documents, such as PDF documents, and grouping text lines into predicted borderless tables. The target document comprises a set of text lines each having a respective vertical and horizontal position in the target document. A sorted list of the text lines is generated based upon a vertical and horizontal position of each text line in the target document. For each text line in the sorted list, a respective probability that the text line in the sorted list belongs to a borderless table is then determined. According to one embodiment, the probability may be determined using a classifier that may employ a logistic regression algorithm.

Abstract: An automatic guided vehicle (AGV) comprising a mobile base including a drive train and configured to drive the AGV in a self-navigation mode within a facility, a first camera configured to capture first image data of objects within the facility, a second camera configured to capture second image data of objects within the facility, the second camera including a content filter, and a main control module configured to receive the first and second image data from the first and second cameras. The main control module executes a recognition neural network program. The neural network program recognizes targets in the first image data. The main control module also executes a supervisor program under user control. The supervisor program is receives the second image data and recognizes markers attached to targets in the second image data. The supervisor program produces a supervised outcome in which targets to which markers are attached are associated with categories based on user commands.

Abstract: Example embodiments described herein therefore relate to an object-model based event detection system that comprises a plurality of sensor devices, to perform operations that include: generating sensor data at the plurality of sensor devices; accessing the sensor data generated by the plurality of sensor devices; detecting an event, or precursor to an event, based on the sensor data, wherein the detected event corresponds to an event category; accessing an object model associated with the event type in response to detecting the event, wherein the object model defines a procedure to be applied by the event detection system to the sensor data; and streaming at least a portion of a plurality of data streams generated by the plurality of sensor devices to a server system based on the procedure, wherein the server system may perform further analysis or visualization based on the portion of the plurality of data streams.

Abstract: Video and corresponding metadata is accessed. Events of interest within the video are identified based on the corresponding metadata, and best scenes are identified based on the identified events of interest. A video summary can be generated including one or more of the identified best scenes. The video summary can be generated using a video summary template with slots corresponding to video clips selected from among sets of candidate video clips. Best scenes can also be identified by receiving an indication of an event of interest within video from a user during the capture of the video. Metadata patterns representing activities identified within video clips can be identified within other videos, which can subsequently be associated with the identified activities.

Abstract: A video feature extraction method and device are provided. The method includes extracting one or more frames from a video object to obtain one or more frames of images, obtaining one or more shift vectors for each of the one or more frames of images, using each of the one or more shift vectors, taking any pixel in each of the one or more frames of images as a starting point, determining a terminal point directed by the one or more shift vectors from the starting point, and determining an image feature of the one or more frames of images according to a difference between the starting point and the terminal point, and determining a video feature of the video object according to the image feature of the one or more frames of images.

Abstract: A method of delay measurement of a network node device is disclosed. The method includes obtaining a node delay value of a current packet when a preset time period starts. The method further includes determining, based on M+1 boundary values of preset M delay intervals, a delay interval in which the node delay value is located, and adding 1 to a value of a delay segment counter corresponding to the delay interval in which the node delay value is located, where M>1, M is a positive integer. The method further includes obtaining a node delay value of a next packet until the preset time period ends. The method further includes determining a cumulative probability Pacc.j that is greater than or equal to a target probability, and obtaining, as a delay threshold, a node delay value having the target probability.

Abstract: One variation of a method for monitoring occupancy in a work area includes, at a sensor block: transitioning from an inactive state into an active state when an output of a motion sensor indicates motion in a work area; during a scan cycle in the active state, recording an image through an optical sensor at a time, detecting a set of humans in the image, detecting a second set of human effects in the image, predicting a second set of humans occupying but absent the work area based on the second set of human effects, and estimating a total occupancy in the work area at the time based on the set of humans and the second set of humans; and transmitting the total occupancy to a remote computer system for update of a scheduler for the work area.

Abstract: A computer-implemented method for ascertaining a need for predictive maintenance for a microscope system. A microscope system, which an image sensor for recording digital images of a sample, recording digital images during regular operation of the microscope system, and providing a digital image as an input data set to an image analysis system, is provided. At least one feature relating to a malfunction of the microscope system during regular operation is determined, a status signal is produced, and a component group of the microscope system for which a maintenance procedure is necessary is determined.

Abstract: A device control apparatus includes an imaging unit configured to capture an image of an occupant in a vehicle, a first recognition unit configured to recognize a posture of the occupant based on the image captured by the imaging unit, a second recognition unit configured to recognize a state of a hand including at least a shape of the hand of the occupant based on the image captured by the imaging unit, a discrimination processing unit configured to specify a device to be controlled and an operation to be executed based on the posture of the occupant recognized by the first recognition unit and the state of the hand recognized by the second recognition unit, and a controller configured to issue a control command corresponding to the specified device to be controlled and the specified operation to be executed.

Abstract: A method includes training a prediction model to forecast a likelihood of curtailment for at least one wind turbine. The prediction model is trained, by a processor system, using historical information and historical instances of curtailment. The method also includes forecasting the likelihood of curtailment for the at least one wind turbine using the trained prediction model. The method also includes outputting the forecasted likelihood.

Abstract: A pattern finding device of embodiments includes a pattern generator, a pattern storage, a pattern selector, a pattern deleter. The pattern generator generates a group of patterns from data including a plurality of items. The pattern storage stores the group of patterns generated by the pattern generator. The pattern selector selects at least one pattern to be deleted from the group of patterns with reference to an evaluated value indicating a change of an item distribution condition in the group of patterns when at least one pattern which is selected as a candidate is excluded from the group of patterns stored in the pattern storage. The pattern deleter deletes the at least one pattern that is selected by the pattern selector from the pattern storage.

Abstract: The present disclosure is directed toward systems and methods that provide users with efficient and effective user experiences when browsing, selecting, or inspecting content items. More specifically, systems and methods described herein provide users the ability to easily and effectively select multiple content items via a single touch gesture (e.g., swipe gesture). Additionally, systems and methods disclosed herein can allow users to select various content items in a selection interface, preview a content item, and return to the selection interface with the previous selections remaining intact. Still further, systems and methods described herein allow users to transition between a content graphical user interface and a selection interface based on touch gestures with content items. Embodiments of the present invention further provide improved navigability by collapsing views of content items.

Abstract: A method for unsupervised image segmentation based on a background likelihood estimation is described herein. The method includes calculating a distance for each pixel in an input image and transforming each distance into a probability of the distance of belonging to a background of an input image or a foreground of the input image. The method also includes transforming each probability into a log likelihood value to form a unary term and minimizing an energy function including the unary term to obtain a set of foreground labels and a set of background labels.

Abstract: The invention discloses a sentence similarity judgment method, which belongs to the technical field of natural language processing.