Abstract: An object tracking method and apparatus are provided. The object tracking method includes detecting a target object in a first-type input image that is based on light in a first wavelength band, tracking the target object in the first-type input image based on detection information of the target object, measuring a reliability of the first-type input image by comparing the first-type image to an image in a database, comparing the reliability of the first-type input image to a threshold, and tracking the target object in a second-type input image that is based on light in a second wavelength band.

Abstract: A computer-implemented method for automatically detecting events and creating photo-product designs based on the events in a photo-product design system includes automatically identifying an event by an event detection module based on daily numbers of captured photos over a plurality of days, automatically selecting a photo-product type by an intelligent product design creation engine in the photo-product design system, calculating a daily weight for a photo product design in the photo-product type based on the daily numbers of captured photos, automatically determining a number of product photos allocated to each day based on associated daily weight, automatically selecting product photos from the captured photos each day at the event according to the number of product photos allocated to each day, and automatically creating a photo-product design for the event using the selected product photos.

Abstract: An electronic device for active learning includes at least one memory and at least one processor coupled to the at least one memory. The at least one processor is configured to select one or more entries from a data set including unlabeled data based on a similarity between the one or more entries and labeled data. The at least one processor is further configured to cause the one or more entries to be labeled.

Abstract: The present invention pertains to a method for automatic sea lice monitoring in fish aquaculture, the method comprising submerging a camera (4) in a sea pen (300) comprising fish, using the camera to make an image of at least one of said fish, analysing the image to differentiate between individual sea lice present on the fish and the fish itself and assessing the number of sea lice present on the fish, wherein the camera is attached to a device (1, 10, 100) for guiding the salmon along an imaging track (5), the camera being directed to the track.

Abstract: An information processing apparatus (100) includes an input unit (102) that inputs a first threshold value and a second threshold value which are threshold values related to a degree of similarity of a feature value of each of a plurality of pieces of data, the first threshold value being for regarding data as belonging to an identical group and the second threshold value being smaller than the first threshold value, and a grouping unit (104) that groups the data by using the degree of similarity, the first threshold value, and the second threshold value, in which the grouping unit (104) causes data of which the degree of similarity with representative data is greater than the first threshold value to be included in the same group, and selects new representative data from among pieces of data of which the degree of similarity with the representative data already present is less than the second threshold value.

Abstract: Techniques for distinguishing objects (e.g., an individual or an individual pushing a shopping cart) are disclosed. An object is detected in images of a scene. A height map is generated from the images, and the object is represented as height values in the height map. Based on height properties associated with another object, it is determined whether the other object is associated with the object. If so determined, the objects are classified separately.

Abstract: A device, apparatus, and method provide logic for processing information. In one implementation, a device may include an image acquisition unit configured to acquire an image, and a transmission unit configured to transmit information associated with the image to an information processing apparatus, such as a server. The server may be associated with a first feature quantity dictionary. The device also may include a receiving unit configured to receive a second feature quantity dictionary from the server in response to the transmission. The second feature quantity dictionary may include less information than the first feature quantity dictionary, and the server may generate the second feature quantity dictionary based on the image information and the first feature quantity dictionary. The device may include an identification unit configured to identify an object within the image using the second feature quantity dictionary.

Abstract: The present disclosure provides an improved approach to implement structure learning of neural networks by exploiting correlations in the data/problem the networks aim to solve. A greedy approach is described that finds bottlenecks of information gain from the bottom convolutional layers all the way to the fully connected layers. Rather than simply making the architecture deeper, additional computation and capacitance is only added where it is required.

Abstract: A processing node in a temporal memory system includes a spatial pooler and a sequence processor. The spatial pooler generates a spatial pooler signal representing similarity between received spatial patterns in an input signal and stored co-occurrence patterns. The spatial pooler signal is represented by a combination of elements that are active or inactive. Each co-occurrence pattern is mapped to different subsets of elements of an input signal. The spatial pooler signal is fed to a sequence processor receiving and processed to learn, recognize and predict temporal sequences in the input signal. The sequence processor includes one or more columns, each column including one or more cells. A subset of columns may be selected by the spatial pooler signal, causing one or more cells in these columns to activate.

Abstract: Automated detection of reasoning in arguments. A training set is generated by: obtaining multiple arguments, each comprising one or more sentences provided as digital text; automatically estimating a probability that each of the arguments includes reasoning, wherein the estimating comprises applying a contextual language model to each of the arguments; automatically labeling as positive examples those of the arguments which have a relatively high probability to include reasoning; and automatically labeling as negative examples those of the arguments which have a relatively low probability to include reasoning. Based on the generated training set, a machine learning classifier is automatically trained to estimate a probability that a new argument includes reasoning. The trained machine learning classifier is applied to the new argument, to estimate a probability that the new argument includes reasoning.

Abstract: There is described a computer-implemented method for generating a vector representation of an image, the computer-implemented method comprising: receiving a given image and semantic information about the given image; generating a first vector representation of the given image using an image embedding method; generating a second vector representation of the semantic information using a word embedding method; combining the first vector representation of the image to be embedded and the second vector representation of the semantic information together, thereby obtaining a modified vector representation for the image to be embedded; and outputting the modified vector representation.

Abstract: A processing system for an unmanned vehicle (UV) such as an unmanned aerial vehicle (UAV) is provided. The processing system comprises a first processing unit of an integrated circuit and a second processing unit of the integrated circuit. The processing system comprises a first operating system provisioned using the first processing unit. The first operating system is configured to execute a first vehicle control process. The processing system comprises a virtualization layer configured using at least the second processing unit, and a second operating system provisioned using the virtualization layer. The second operating system is configured to execute a second vehicle control process.

Abstract: An electronic device according to various embodiments, may include a camera, a communication circuit, a display and a processor, and the processor may be configured to acquire an image of an external object, transmit the image to an external electronic device, so that the external electronic device transmits product information related to the external object included in the image to the electronic device, using the communication circuit, determine one or more keywords related to the product information transmitted from the external electronic device, identify preference category information and preference brand information of a user, based on a usage record related to a product of the user related to the electronic device, determine weights for the one or more keywords, using the preference category information and the preference brand information, and provide at least some keywords having weights which satisfy a specified condition among the one or more keywords, on the display together with the product info

Abstract: Methods and devices for manipulating an image are described. The method comprises receiving image data, the image data including a first image obtained from a first camera and a second image obtained from a second camera, the first camera and the second camera being oriented in a common direction; identifying one or more boundaries of an object in the image data by analyzing the first image and the second image; and displaying a manipulated image based on the image data, wherein the manipulated image includes manipulation of at least a portion of the first image based on boundaries of the object.

Abstract: A system and method for inserting a composited image or otherwise generated graphic into a selected video by way of a programmatic process. According to some embodiments, a system may comprise an Automated Placement Opportunity Identification (APOI) engine, a Placement Insertion Interface (PII) engine, a preview system, and an automated compositing service. The system finalizes a graphic composite into a video and provides a user with a preview for final export or further manipulation.

Abstract: Various disclosed embodiments are directed to classify or determining an image style of a target image according to a consumer application based on determining a similarity score between the image style of a target image and one or more other predetermined image styles of the consumer application. Various disclosed embodiments can resolve image style transfer destructiveness functionality by making various layers of predetermined image styles modifiable. Further various embodiments resolve tedious manual user input requirements and reduce computing resource consumption, among other things.

Abstract: A computer-implemented method for annotating images is disclosed. The computer-implemented method includes generating a saliency map corresponding to an input image, wherein the input image is an image that requires annotation, generating a behavior saliency map, wherein the behavior saliency map is a saliency map formed from an average of a plurality of objects contained within respective bounding boxes of a plurality of sample images, generating a historical saliency map, wherein the historical saliency map is a saliency map formed from an average of a plurality of tagged objects in the plurality of sample images, fusing the saliency map corresponding to the input image, the behavior saliency map, and the historical saliency map to form a fused saliency map, and generating, based on the fused saliency map, a bounding box around an object in the input image.

Abstract: Methods, systems, and computer programs are presented for adding new features to a network service. A method includes receiving an image depicting an object of interest. A category set is determined for the object of interest and an image signature is generated for the image. Using the category set and the image signature, the method identifies a set of publications within a publication database and assigns a rank to each publication. The method causes presentation of the ranked list of publications at a computing device from which the image was received.

Abstract: Systems and methods are disclosed for applying neural networks in resource-constrained environments. A system may include a sensor located in a resource-constrained environment configured to generate sensor data of the resource-constrained environment. The system may also include a first computing device not located in the resource-constrained environment configured to produce a neural network structure based on the sensor data. The system may further include a second computing device located in the resource-constrained environment configured to provide the sensor data as input to the neural network structure. The second computing device may be further configured to determine a state of the resource-constrained environment based on the input of the sensor data to the neural network structure.

Abstract: In one embodiment, the present disclosure is directed to a method of verifying a location of an organization. The method includes providing a user interface to a device of a representative of an organization, the user interface prompting the representative to provide organization data. The organization data includes organization name data indicative of an organization name, organization address data indicative of a location of the organization, photograph files for photographs of specific different portions of the location of the organization, and photograph location data indicative of where each of the photographs was taken. The method further includes receiving the organization data from the device, and verifying that the organization address data corresponds with the organization address data.

Abstract: A system for controlling a physical system via segmentation of an image includes a controller. The controller may be configured to receive an image of n pixels from a first sensor, and an annotation of the image from a second sensor, form a coupling matrix, k class vectors each of length n, and a bias coefficient based on the image and the annotation, generate n pixel vectors each of length n based on the coupling matrix, class vectors, and bias coefficient create a single segmentation vector of length n from the pixel vectors wherein each entry in the segmentation vector identifies one of the k class vectors, output the single segmentation vector; and operate the physical system based on the single segmentation vector.

Abstract: An image processing apparatus includes: a receiving unit configured to receive an addition instruction for adding a page to album data including a plurality of pages; an image obtaining unit configured to obtain a user selection image as an image to be arranged in the page to be added in response to the addition instruction, the user selection image being selected by a user; a first analysis information obtaining unit configured to obtain analysis information of the user selection image; and a selecting unit configured to select an image to be arranged in the added page other than the user selection image, based on the analysis information of the user selection image.

Abstract: Generating a controllable panoramic image while eliminating unsuitable dynamic elements by receiving a plurality of images of a location from a user device, wherein the plurality of images includes images of a location at various times, identifying an object of one or more images of the plurality of images, wherein the object corresponds to an unsuitable condition for a database, determining a score of the one or more images of the plurality of images based at least in part on the identified object, determining a base image from the one or more images of the plurality of images, and generating a set of replacement images of the location based at least in part on respective determined scores of the one or more images of the plurality of images.

Abstract: In various example embodiments, a system and method for determining an item that has confirmed characteristics are described herein. An image that depicts an object is received from a client device. Structured data that corresponds to characteristics of one or more items are retrieved. A set of characteristics is determined, the set of characteristics being predicted to match with the object. An interface that includes a request for confirmation of the set of characteristics is generated. The interface is displayed on the client device. Confirmation that at least one characteristic from the set of characteristics matches with the object depicted in the image is received from the client device.

Abstract: An information processing system comprises an image capturing apparatus and an information processing apparatus, the image capturing apparatus includes an image capturing device; a first evaluation unit configured to perform first evaluation on a captured image; and a first transmission unit configured to transmit the captured image to the information processing apparatus, and the information processing apparatus includes a reception unit configured to receive the captured image; a second evaluation unit configured to perform second evaluation on the captured image; and a second transmission unit configured to transmit an evaluation result to the image capturing apparatus, the image capturing apparatus further including a sorting unit configured to receive the evaluation result of the second evaluation, and sort the captured image using an evaluation results of the first evaluation and the second evaluation.

Abstract: Machine learning-based techniques for summarizing collections of data such as image and video data leveraging side information obtained from related (e.g., video) data are provided. In one aspect, a method for video summarization includes: obtaining related videos having content related to a target video; and creating a summary of the target video using information provided by the target video and side information provided by the related videos to select portions of the target video to include in the summary. The side information can include video data, still image data, text, comments, natural language descriptions, and combinations thereof.

Abstract: A diagnostic tool for deep learning similarity models and image classifiers provides valuable insight into neural network decision-making. A disclosed solution generates a saliency map by: receiving a baseline image and a test image; determining, with a convolutional neural network (CNN), a first similarity between the baseline image and the test image; based on at least determining the first similarity, determining, for the test image, a first activation map for at least one CNN layer; based on at least determining the first similarity, determining, for the test image, a first gradient map for the at least one CNN layer; and generating a first saliency map as an element-wise function of the first activation map and the first gradient map. Some examples further determine a region of interest (ROI) in the first saliency map, cropping the test image to an area corresponding to the ROI, and determine a refined similarity score.

Abstract: This disclosure discloses a method and apparatus for generating a machine learning model.

Abstract: A tool for predicting that a person is likely to be abnormally hydrated over a future time interval, and in some cases to alert the person or a medical professional to intervene. From a series of physiological measurements, a tissue electrical impedance spectrum curve, which comprises a phase spectrum curve in an embodiment, is determined and changes in the shape of the curve are ascertained. The measurements may be received using one or more sensors worn by the person. In some embodiments, current and historic spectrum curvature are applied to an evolutionary algorithm, such as particle-swarm optimization (PSO) or differential evolution (DE), to determine an inference regarding the persons future hydration status. In one embodiment, a statistical forecast for the next epoch immediately beyond the present one, is determined.

Abstract: A method, a computer system, and a computer program product are provided for federated learning enhanced with semantic learning. An aggregator may receive cluster information from distributed computing devices. The cluster information may relate to identified clusters in sample data of the distributed computing devices. The aggregator may integrate the cluster information to define classes. The integrating may include identifying any redundant clusters amongst the identified clusters. A number of the classes may correspond to a total number of the clusters from the distributed computing devices reduced by any redundant clusters. A deep learning model may be sent from the aggregator to the distributed computing devices. The deep learning model may include an output layer having nodes that may correspond to the defined classes. The aggregator may receive results of federated learning performed by the distributed computing devices. The federated learning may train the deep learning model.

Abstract: A method for automatically controlling an emotional environment in a vehicle is provided. The method includes generating reflected wave information by radiating an electromagnetic wave toward a rear seat of the vehicle and receiving a reflected wave. A degree of activity is determined based on the reflected wave information and at least one device installed within the vehicle is operated based on the degree of activity.

Abstract: Big data acquisition and analysis system using intelligent image recognition, and application method thereof are provided. The system includes an intelligent cloud server, wherein the intelligent cloud server includes a computation server and a storage server, the computation server is equipped with an image recognition system which includes a data reading module, a video stream data processing module, an AI image recognition module, a data storage module and a model tuning module, and the storage server is provided with a video stream storage database, a video stream management module and a data center database that are interactively connected. In embodiments of the present disclosure, consumers' non-private actual digital behaviors are restored to produce more commercial value. This process realizes real-time digital behavior analysis of consumers, enables business analysis to be closer to reality, brings more valuable analysis results to brands, and guides the brands to optimize consumption paths globally.

Abstract: A method of identifying an object of interest can comprise obtaining first samples of an intensity distribution of one or more object of interest, obtaining second samples of an intensity distribution of confounder objects, transforming the first and second samples into an appropriate first space, performing dimension reduction on the transformed first and second samples, whereby the dimension reduction of the transformed first and second samples generates an object detector, transforming one or more of the digital images into the first space, performing dimension reduction on the transformed digital images, whereby the dimension reduction of the transformed digital images generates one or more reduced images, classifying one or more pixels of the one or more reduced images based on a comparison with the object detector, and identifying one or more objects of interest from the classified pixels.

Abstract: A facial images retrieval system is provided. The facial images retrieval system is adapted to receive an initial textual description of a facial image to perform an initial facial image search that obtains a plurality of facial images based on the textual description. The facial images retrieval system then receives a selection of the first and second facial images that are relatively close to a desired facial image to perform a further facial image search to obtain another facial image.

Abstract: A system and method for determining an absolute position of an object in an area is presented. The system includes a server having a processor, and a plurality of camera nodes coupled to the server. Each node includes a camera that acquires images of the object and area. The server receives image data from a camera, detects the object within an approximate location by image analysis techniques, and determines a relative position of the object in pixel coordinates. The processor then detects stationary markers proximate to the relative location of the object, determines an absolute position of the detected markers relative to known markers to define an absolute position of the marker, and determines an absolute location of the object in relation to the absolute location of the detected marker. This absolute position of the object is provided to an official to accurately locate the object in the area.

Abstract: A framework in which annotated images can be analyzed in small batches to learn and distinguish between higher-quality annotations and lower-quality annotations, especially in the case of manual annotations for which quality assurance is desired. This framework is extremely generalizable and can be used for indoor images, outdoor images, medical images, etc., without limitation. An echo state network (ESN) is provided as a special case of semantic segmentation model that can be trained using as few as tens of annotated images to predict semantic regions and provide metrics that can be used to distinguish between higher-quality annotations and lower-quality annotations.

Abstract: Managing a display of an information handling system, including: identifying a first magnitude of a frame rate of a display coupled to an information handling system; detecting an ambient light level of a physical environment surrounding the information handling system; determining that the ambient light level of the physical environment surrounding the information handling system is below a first threshold; in response to determining that the ambient light level of the physical environment surrounding the information handling system is below the first threshold: identifying a second magnitude of the frame rate of the display that corresponds to the ambient light level, wherein the second magnitude is a flicker fusion rate of the display for the ambient light level of the physical environment surrounding the information handling system, wherein the second magnitude is less than the first magnitude; and reducing the frame rate of the display to the second magnitude.

Abstract: The disclosure provides a visual positioning method and apparatus, an electronic device and a computer-readable storage medium. The method includes: generating a semantic graph by semantically identifying collected images; determining description information of each entity through a random walk algorithm in the established semantic graph; determining candidate entities matching each entity in a preset entity map based on the description information; and positioning a collection area of the current image based on an area where the candidate entities are located in the preset entity map. The description information of each entity node constructed with the random walk algorithm not only contains semantic information of the corresponding node, but also local constraint information between semantics.

Abstract: Various approaches discussed herein enable browsing groups of visually similar items to an item of interest, wherein the item of interest may be identified in a query image, for example. One or more visual attributes associated with the item of interest are identified, and the visually similar items matching at least one of the visual attributes are grouped together, wherein the group is ranked according to the visually similar items' overall visual similarity to the item of interest, for example by using a visual similarity score and/or metric.

Abstract: Data stream processing is performed. For instance, a method includes: in response to a query request on an input data stream, determining data labels for input data items in the input data stream, the data labels at least indicating a first matching relationship between the input data items and a first query condition of the query request; determining an output data stream corresponding to the input data stream, the output data stream including output data items corresponding to the input data items, and each output data item having a data label; and determining query information corresponding to the query request based on the output data stream. In this way, it is possible to respond to real-time query requests for data streams.

Abstract: Aspects of the subject disclosure may include, for example, receiving information about a content item of interest to a content consumer, determining a context of the content consumer, curating a summary segment for the content consumer based on the context of the content consumer, and presenting the summary segment to the content consumer at a context-appropriate time and in a context-appropriate manner to orient the content consumer to the content item of interest at a current viewing time of the content consumer. Other embodiments are disclosed.

Abstract: Systems and methods for detection and localization of image and document forgery. The method can include the step of receiving a dataset having a plurality of authentic images and a plurality of manipulated images. The method can also include the step of benchmarking a plurality of image forgery algorithms using the dataset. The method can further include the step of generating a plurality of receiver operating characteristic (ROC) curves for each of the plurality of image forgery algorithms. The method also includes the step of calculating a plurality of area under curve metrics for each of the plurality of ROC curves. The method further includes the step of training a neural network for image forgery based on the plurality of area under curve metrics.

Abstract: There is provided a barcode detection device including an image sensor and a processor. The image sensor captures an image frame of a color barcode. The processor sequentially processes every row of the image frame to find at least one color segment in each row of the image frame, categorizes color segments of a same color in one cluster according to a position relationship and a color similarity of the color segments in the image frame, and averages color parameters of pixels in one cluster to accordingly recognize a color of the pixels in said one cluster.

Abstract: A system and method for imaging a biological sample using a freezable fluid cell system is disclosed. The freezable fluid cell comprises a top chip, a bottom chip, and a spacer to control the thickness of a vitrified biological sample. The spacer is positioned between the top chip and the bottom chip to define a channel that is in fluid communication with an inlet port and an exit port to the freezable fluid cell system. The channel can be filled with a biological sample, vitrified, and imaged to produce high-resolution electron microscopic image.

Abstract: An approach is provided for filtering imagery to train a feature detection model. The approach involves, for example, receiving a plurality of images. The plurality of images is classified as depicting a feature of interest. The approach also involves providing data for presenting a bulk arrangement of at least one subset of the plurality of images, wherein the bulk arrangement is based on a characteristic of the plurality of images (e.g., detection confidence, position, size, visual characteristic, etc. of the detected feature). The approach further involves initiating a filtering of the plurality of images based on the bulk arrangement and providing the filtered plurality of images as training data to train the feature detection model.

Abstract: Systems and methods for detecting and classifying clinical features in medical images are disclosed. Natural language processes are applied to speech received from a dictation system to determine clinical and anatomical information for a medical image being viewed. In some examples, gaze location information identifying an eye position is received, as well as an image position for the medical image being viewed. Features of the medical image are detected and classified based on machine learning models. Anatomical associations are generated based on one or more of the classifications, the anatomical information, the gaze information, and the image position. The machine learning models can be trained based on the anatomical associations. In some examples, reports are generated based on the anatomical associations.

Abstract: This application discloses a method and an apparatus for training a classification model. The method includes obtaining a training sample, the training sample including a training parameter and a true classification corresponding to the training parameter and preforming classification training on an initial classification model by using the training parameter, to obtain a predicted classification. The method also includes determining a residual between the true classification and the predicted classification according to a gradient loss function of the initial classification model, the gradient loss function comprising a distance factor representing a distance between a first category and a second category, the first category being a category to which the predicted classification belongs, and the second category being a category to which the true classification belongs. The method further includes modifying the initial classification model according to the residual to obtain a final classification model.

Abstract: A system for providing cognition assistance including a contextual memory trainer, which receives preprocessed data including facial data, scene data, and activity data related to a video in association with temporal data and geographical location data of the camera that captured the video, where the scene data, the activity data, the geographical location data, and the temporal data collectively define spatiotemporal data. The trainer identifies an unknown aspect in the preprocessed data based on historical data and determines a predefined priority factor therefor. The priority factor includes one of a frequency of occurrence within a set period and relative proximity of the unknown aspect to the camera, a known face, place, or scene. The unknown aspect is prioritized for annotation based on a value of the priority factor exceeding a predefined threshold value, based on which facial data is associated with the spatiotemporal data to provide contextual annotated data.

Abstract: A position and pose determination unit (103) is configured to determine a position and an pose of the video acquisition unit (110) in such a way that a level of hiding caused by overlapping of objects becomes low based on environmental object information indicating an environmental object including a structural object present in the monitored area and a placed object placed in the structural object, and staying characteristic information indicating a staying characteristic of the object determined depending on the environmental object. The analysis and display unit (111) is configured to perform at least one of analyzing a video captured by the video acquisition unit (103) at the position and the pose determined by the position and pose determination unit (110) and displaying the video.

Abstract: A data linking system is described herein that links data records corresponding to a particular real estate property even if there are inconsistencies in the data records, the physical presence of the real estate property has changed over time, and/or the data records use different terminology. In some cases the data records are matched using a trained machine learning model. The data linking system can optionally generate a visualization of the data record linkage via interactive user interfaces. By linking data records despite the issues described above, the data linking system reduces the number of navigational steps a user performs to obtain data associated with a property and/or reduces data processing times. The disclosed system may be used to generate and maintain a comprehensive database of substantially all properties within a jurisdiction, in which a unique identifier is assigned to each property.