Abstract: A method and an apparatus for recognizing a specific object inside an image in an electronic device are provided. The method includes displaying at least one image; detecting at least one gesture; selecting a recognition function related to at least one object existing in the at least one image according to the detected at least one gesture; and recognizing the at least one object using the selected recognition function.

Abstract: A role-based information distribution system, in some embodiments, comprises a display to provide an image containing multiple dynamic icons. It further comprises a wearable device camera to capture the image, and processing logic, coupled to the camera, to interpret the multiple dynamic icons and to provide information pertaining to a selected one or more of the multiple dynamic icons to a user via the wearable device. The processing logic selects the selected one or more of the multiple dynamic icons based on a role associated with the user.

Abstract: According to one embodiment, a system includes a wearable device on a head of a user and including a display in a line of vision of the user, a first detector configured to detect a movement of the user, a second detector configured to detect a state of an apparatus operated by the user, and a server connected to the wearable device, the first detector and the second detector. The server is configured to display information about work contents of the user on the display based on a detection result of the first detector and a detection result of the second detector.

Abstract: According to one embodiment, a system includes a wearable device on a head of a user and including a display in a line of vision of the user, a first detector configured to detect a movement of the user, a second detector configured to detect a state of an apparatus operated by the user, and a server connected to the wearable device, the first detector and the second detector. The server is configured to display information about work contents of the user on the display based on a detection result of the first detector and a detection result of the second detector.

Abstract: According to one embodiment, a system includes a wearable device on a head of a user and including a display in a line of vision of the user, a first detector configured to detect a movement of the user, a second detector configured to detect a state of an apparatus operated by the user, and a server connected to the wearable device, the first detector and the second detector. The server is configured to display information about work contents of the user on the display based on a detection result of the first detector and a detection result of the second detector.

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. Events of interest can be tagged within the video based on, for instance, user input, audio signals, motion vectors, and metadata corresponding to the video. A camera system can process video data based on the events of interest tagged within the video before outputting the video data. For instance, video scenes associated with tagged events of interest can be combined to form a video highlight clip. Likewise, portions of video tagged with events of interest can be encoded or stored at a higher resolution or frame rate than other portions of the video.

Abstract: Systems for monitoring a confined space include image sensors, such as cameras, and access control devices, such as intercoms and scanning devices, positioned within the interior and external to the confined space. Sensors for detecting hazardous materials, light sources, and audio output devices, such as speakers, may also be positioned within the confined space. Equipment within the confined space may be explosion proof or intrinsically safe and rated for use in hazardous areas. A first single electrical cable, such as a multi-core cable, may engage all of the system components external to the confined space to power components. A second single electrical cable may engage all of the components within the confined space to the power components. A monitoring station may receive video, audio, sensor, and access data from the system equipment and generate alarms and notifications responsive to unauthorized access attempts, hazardous materials, or irregular user incidents.

Abstract: The present invention provides a crowd monitoring system with which it is possible to obtain a crowd density accurately, irrespective of the congestion state. This crowd monitoring system 100 is provided with: an image acquiring unit 101 which acquires a plurality of images; an arithmetic logic unit 108; and a storage unit 106 which stores information relating to relationships between image feature quantities and an object density, acquired in advance, and information relating to relationships between motion feature quantities and the object density. The arithmetic logic unit 108 comprises: an image feature quantity acquiring unit 103 which obtains image feature quantities of objects in the acquired images; a motion line acquiring unit 104 which obtains motion lines of the objects in the acquired images; a motion feature quantity acquiring unit 105 which obtains motion feature quantities of the objects on the basis of the obtained motion lines; and a crowd density acquiring unit 107.

Abstract: An analysis method of lane stripe images, an image analysis device and a non-transitory computer readable medium thereof are provided to perform steps of: setting a reference point as a center to recognize the lane stripe image in a plurality of default directions; defining a plurality of preset sections onto the lane stripe image and determining a characteristic value of the lane stripe image in each of the preset sections whenever the lane stripe image is recognized in one of the default directions; determining a first feature parameter according to the characteristic values of the lane stripe image in the preset sections when the lane stripe image is recognized in at least one of the default directions; and determining an actual lane parameter of the lane stripe image according to at least the first feature parameter.

Abstract: A travel control device for a vehicle is configured to execute a self-driving control based on a traveling state and traveling environment information of the vehicle. The travel control device includes a controller. The controller estimates execution of a right turn and a left turn from a traveling lane of the vehicle based on the traveling state and traveling environment information. When execution of either one of the right turn and the left turn from the traveling lane of the vehicle is estimated, the controller varies a traveling path from the traveling lane to a lane after the execution of the estimated turn according to the traveling state and traveling environment information to perform a right or left turn control of the vehicle.

Abstract: Certain embodiments of the invention may include systems, methods, and apparatus for in-vehicle fiducial mark tracking and interpretation According to an example embodiment of the invention, a method is provided for executing computer executable instructions by one or more processors. The method includes receiving the one or more images from at least one camera attached to a vehicle; selecting, from the one or more received images, a region of interest associated with an object in the vehicle; identifying fiducial marks within the selected region of interest by comparing the identified fiducial marks with one or more stored fiducial representations; determining, based at least in part on the comparison, spatial information associated with the object or an occupant of the vehicle; and sending information based at least in part on the determined spatial information.

Abstract: Provided is a behavior recognition apparatus, including a detection unit configured to detect, based on a vehicle interior image obtained by photographing a vehicle interior, positions of a plurality of body parts of a person inside a vehicle in the vehicle interior image; a feature extraction unit configured to extract a rank-order feature which is a feature based on a rank-order of a magnitude of a distance between parts obtained by the detection unit; and a discrimination unit configured to discriminate a behavior of an occupant in the vehicle using a discriminator learned in advance and the rank-order feature extracted by the feature extraction unit. Also provided is a learning apparatus to learn the discrimination unit.

Abstract: Disclosed are a mobile device and controlling method thereof. The present invention includes a memory configured to register a first iris image, an illumination sensor configured to sense an external illuminance of the mobile device, a display configured to emit a light from a preset region, a camera configured to detect either a second iris image or a pupil image, and a controller configured to control the memory, the illumination sensor, the camera and the display and control the display to display a message for guiding a change of an eye according to the external illuminance sensed by the illumination sensor, wherein the message for guiding the change of the eye is changed according to the sensed external illuminance.

Abstract: Embodiments of the present invention may provide the capability to identify a specific object being interacted with that may be cheaply and easily included in mass-produced objects. In an embodiment, a computer-implemented method for object identification may comprise receiving a signal produced by a physical interaction with an object to be identified, the signal produced by an identification structure coupled to the object during physical interaction with the object, processing the signal to form digital data representing the signal, and accessing a database using the digital data to retrieve information identifying the object.

Abstract: The page straightening system includes a word module to determine an enclosing quadrilateral of each connected component of curved page content. Further, a line module in the page straightening system is configured to form text lines by joining enclosing quadrilaterals based on a reading order. Subsequently, a correction module in the page straightening system is configured to generate straightened content from the curved content based on the text lines. As such, the page straightening system can automatically straighten curved page content.

Abstract: In an example embodiment a method, apparatus and computer program product are provided. The method includes facilitating simultaneous capture of a first image by a first camera and a second image by a second camera associated with a device. One or more distortion parameters associated with a distortion in the second image may be determined based on a comparison of the second image with at least one template image associated with the second image. A distortion-free first image is generated based on the one or more distortion parameters associated with the second image by performing one of applying the one or more distortion parameters to the first image, and estimating one or more distortion parameters associated with the first image based on the one or more distortion parameters associated with the second image, and applying, the one or more distortion parameters associated with the first image to the first image.

Abstract: Methods, apparatuses and systems may provide for a neural network that analyzes and classifies agricultural conditions based on depth data and color data recorded by one or more drones, and generates an annotated three dimensional (3D) map with the agricultural conditions. Additionally, an object recognition model may be trained for use by a drone controller to trigger drones to conduct a collection of depth data at an increased proximity to crop-related objects based on agricultural conditions.

Abstract: An object recognition device includes an acquisition unit configured to acquire a recognition target image that serves as an object to be recognized; a retrieval unit configured to search an image database storing a plurality of image data in association with tag information and retrieve a similar image that matches the recognition target image; and a recognition unit configured to recognize the object included in the recognition target image on the basis of tag information associated with a similar image obtained by the retrieval unit. The recognition may select the tag information that appears most frequently among the tag information associated with the similar images as a recognition result. The recognition unit may also compute a tag information reliability score from the similar image in the retrieval result and recognize an object taking into account said reliability score.

Abstract: A computer-implemented method generates a multimodal digital image by processing a vector with a first neural network to produce a first modality of the digital image and processing the vector with a second neural network to produce a second modality of the digital image. A structure and a number of layers of the first neural network are identical to a structure and a number of layers of the second neural network. Also, at least one layer in the first neural network has parameters identical to parameters of a corresponding layer in the second neural network, and at least one layer in the first neural network has parameters different from parameters of a corresponding layer in the second neural network.

Abstract: According to an example aspect of the present invention, there is provided an apparatus comprising at least one processing core and at least one memory including computer program code, the at least one memory and the computer program code being configured to, with the at least one processing core, cause the apparatus at least to nm a convolutional neural network comprising an input layer arranged to provide signals to a first convolutional layer and a last convolutional layer, run a first intermediate classifier, the first intermediate classifier operating on a set of feature maps of the first convolutional layer, and decide to abort or to continue processing of a signal set based on a decision of the first intermediate classifier.

Abstract: Systems and methods for determining optimized imaging parameters for imaging a patient include learning a model of a relationship between known imaging parameters and a quality measure, the known imaging parameters and the quality measure being determined from training data. Optimized imaging parameters are determined by optimizing the quality measure using the learned model. Images of the patient are acquired using the optimized imaging parameters.

Abstract: A method for providing a singling device of a storage and dispensing container for drug portions is provided. A singling device is adapted to a specific drug portion based on the measurement of the drug portion. The measurement is obtained by generating at least one image of a to-be-measured drug portion by a detection device and using image analysis to process the at least one image. Drug information for the specific drug portion is determined, the drug information including at least the dimensions of the specific drug portion. Based on the determined drug information, a singling device fitting the drug portion to be singularized is identified and provided for use in the storage and dispensing container. A system for identifying a singling device is also provided.

Abstract: Methods, apparatus, and other embodiments predict response to pemetrexed based chemotherapy. One example apparatus includes an image acquisition circuit that acquires a radiological image of a region of tissue demonstrating NSCLC that includes a region of interest (ROI) defining a tumoral volume, a peritumoral volume definition circuit that defines a peritumoral volume based on the boundary of the ROI and a distance, a feature extraction circuit that extracts a set of discriminative tumoral features from the tumoral volume, and a set of discriminative peritumoral features from the peritumoral volume, and a classification circuit that classifies the ROI as a responder or a non-responder using a machine learning classifier based, at least in part, on the set of discriminative tumoral features and the set of discriminative peritumoral features.

Abstract: Embodiments include a system, method, and computer program product for distributed intelligent pattern recognition. Embodiments include a cooperative multi-agent detection system that enables an array of disjunctive devices (e.g., cameras, sensors) to selectively cooperate to identify objects of interest over time and space, and to contribute an object of interest to a shared deep learning pattern recognition system based on a bidirectional feedback mechanism. Embodiments provide updated information and/or algorithms to one or more agencies for local system learning and pattern updating recognition models. Each of the multiple agencies may in turn, update devices (e.g., cameras, sensors) coupled to the local machine learning and pattern recognition models.

Abstract: A system and method are provided for performing saliency detection on an image or video. The method includes training and creating deep features using deep neural networks, such that an input image is transformed into a plurality of regions, which minimizes intra-class variance, and maximizes inter-class variance, according to one or more active contour energy constraints. The method also includes providing and output associated with the deep features.

Abstract: A processing apparatus includes: a processing unit that performs a process related to image data; a display unit that displays a process selection portion, with which the process performed by the processing unit is associated and which is selected to start the process by the processing unit; and a creation unit that, in a case of creating the process selection portion to be displayed in the display unit, creates the process selection portion while associating data with the process selection portion.

Abstract: A method according to one embodiment includes receiving Radio Frequency Identification (RFID) tag information associated with a vehicle, the RFID tag information including registration information for the vehicle, monetary information associated with the vehicle, and a service history of the vehicle, performing an identification, utilizing the RFID tag information, and determining one or more obligations associated with the vehicle, based on the identification.

Abstract: A bio-electronic tag-based feature extraction and verification method, a device therefor and a tag.

Abstract: An RFID tag includes: a flexible, sheet-shaped substrate; an antenna pattern that is formed on the substrate; an IC chip that is mounted on the substrate and that is connected to the antenna pattern; an adhesive member that adheres the IC chip to the substrate; and a reinforcement member that covers the IC chip and the adhesive, and that is at a position such that a central portion of the reinforcement member is offset along a length direction of the substrate with respect to the IC chip and the adhesive member.

Abstract: A system for locating an asset can include a first visible light communication (VLC) device having a first controller, a first transceiver, and a first light source, where the first transceiver has a first range, where the first controller broadcasts, using the first transceiver, a first communication signal, where the first communication signal comprises an identification of the asset. The system can also include an asset communication device associated with the asset, where the asset communication device includes a second transceiver and a second controller, where the second transceiver has a second range, where the asset communication device is within the first range, where the second controller broadcasts, using the second transceiver, a second communication signal in response to the first communication signal, where the second communication signal comprises the identification of the asset.

Abstract: Ising devices interconnected via buses each include: neuron circuits that each update, when a value of an output signal from one of connection destination neuron circuits changes, a value based on an update signal; a memory holding connection destination information wherein items of address information respectively identifying the destination neuron circuits and the ising devices including these circuits and identification information about weight values are associated with each other; a control circuit that outputs, when an output signal of a destination neuron circuit in an ising device other than the own ising device changes, the value of the changed output signal and the update signal based on the destination information; and a router that receives a mode set value from a control device and determines whether to connect at least two neighboring ising devices, or a neighboring ising device and the control circuit, based on the set value.

Abstract: Disclosed is an apparatus for generating an artificial-neural-network-based prediction model. The apparatus includes an input data conversion unit configured to convert input data of an L-dimensional array (L is a natural number) into normalized vector data and input the normalized vector data, a modeling unit configured to model an artificial-neural-network-based prediction model for learning the input vector data and output a value predicted through the modeling, and an adjustment unit configured to compare the value predicted by the modeling unit with an actually measured value to calculate an error value and adjust learning parameters of an artificial neural network using the error value and a back-propagation algorithm.

Abstract: An individual neuron circuit calculates a first value based on a sum of products each obtained by multiplying one of weight values, each representing connection or disconnection between a corresponding neuron circuit and one of the other neuron circuits, by a corresponding one of output signals of the other neuron circuits and outputs 0 or 1, based on a result of comparison between a second value obtained by adding a noise value to the first value and a threshold. An arbitration circuit allows, when first output signals of first neuron circuits interconnected among the neuron circuits simultaneously change based on the weight values, updating of only one of the first output signals of the first neuron circuits and allows, when second output signals of second neuron circuits not interconnected simultaneously change, updating of the second output signals.

Abstract: Various Reservoir Computing systems and a method performed by a Reservoir Computing system are provided. A Reservoir Computing system includes a laser for emitting light. The Reservoir Computing system further includes a mirror for reflecting external feedback light back to the laser. The Reservoir Computing system also includes a modulator for modulating the external feedback light reflected back to the laser. The Reservoir Computing system additionally includes a photo-detector for converting a laser output signal to an electrical signal. The Reservoir Computing system further includes an analog-to-digital converter for sampling the electrical signal. The Reservoir Computing system also includes a controller for applying a learning algorithm to the sampled electrical signal.

Abstract: Non-limiting examples of the present disclosure describe query classification to identify appropriateness of a query. A query may be received by at least one processing device. A deep neural network (DNN) model may be applied to evaluate the query. A vector representation may be generated for query based on application of the DNN model, where the DNN model is trained to classify queries according to a plurality of categories of appropriateness. The DNN model may be utilized to classify the query in a category of appropriateness based on analysis of the vector representation. In one example, auto-complete suggestions for the query may be filtered based on the classification of the category of appropriateness. In another example, classification of the query may be provided to an entry point. In yet another example, a response to the query is managed based on the classification of the query. Other examples are also described.

Abstract: Methods and systems for training a neural network are provided. One system includes one or more components executed by one or more computer subsystems. The one or more components include a neural network configured for determining inverted features of input images in a training set for a specimen input to the neural network, a forward physical model configured for reconstructing the input images from the inverted features thereby generating a set of output images corresponding to the input images in the training set, and a residue layer configured for determining differences between the input images in the training set and their corresponding output images in the set. The one or more computer subsystems are configured for altering one or more parameters of the neural network based on the determined differences thereby training the neural network.

Abstract: Embodiments relate to systems, devices, and computing-implemented methods for generating domain name suggestions by obtaining a domain name suggestion input that includes textual data, segmenting the textual data into tokens, obtaining a list of possible affixes to the textual data, determining conditional probabilities for the possible affixes using a language model, ranking the list of possible affixes based on the conditional probabilities to generate a ranked list of affixes, and generating domain name suggestions based on the ranked list of affixes.

Abstract: A method of processing data by one or more data processing systems for classification of the processed data into one or more predefined classifications, the method comprising: receiving by one or more data processing systems social profile data; binding by the one or more data processing systems based on the input social profile data, values of one or more attributes included in the social profile data to one or more parameters of a classifier executing on the one or more data processing systems; classifying data representing the user into one or more predefined classifications; for one of the predefined classifications into which the data representing the user is classified, identifying by the one or more data processing systems a candidate action included in the predefined classification and unassociated with the user; and transmitting an alert to notify the user of the candidate action.

Abstract: A passenger's activity at the normal entry and exit points to the transit system may be recorded and linked, using a transit ticking system, along with the passenger's transit time and onward travel mode (bike hire, taxi, etc.). These records can be linked to other parameters such as the time, day of the week, season of the year, weather, and/or other such parameters. Furthermore, the passenger may use the transit ticketing system to make onward travel reservations such a bike hire or taxi. Such reservations will also be linked with the entry and exit and other parameters. The passenger's entry and exit on subsequent visits may be recorded and aggregated with past travel parameters. Thus, when a user enters the transit system, the records for that user can be used to predict how long they may be in transit, where they may exit the transit system, and what type of onward travel they may use.

Abstract: Certain example embodiments described herein relate to techniques for managing “bad” or “imperfect” data being imported into a database system. That is, certain example embodiments provide a lifecycle technology solution that helps receive data from a variety of different data sources of a variety of known and/or unknown formats, standardize it, fit it to a known taxonomy through model-assisted classification, store it to a database in a manner that is consistent with the taxonomy, and allow it to be queried for a variety of different usages. Some or all of the disclosed technology concerning auto-classification, enrichment, clustering model and model stacks, and/or the like, may be used in these and/or other regards.

Abstract: A system, method and a computer program product may be provided for automatically creating and parameterizing a semantically-enriched diagnosis model for an entity. The system receives a list of data points, from sensors or a database, to be used to create a diagnosis model. The system automatically creates the diagnosis model based on the received list of data points and data stored in a database and parameterizes the diagnosis model. The parameterized diagnosis model reflects rules that determine one or more potential causes of one or more abnormalities of one or more physical conditions in the entity.

Abstract: A method for estimating a brain activity response following a stimulus of a person comprises the steps: providing a usage data set of the person from a personal device used by said person, wherein at least one usage attribute is associated to said usage data set, wherein attribute data is associated to each of the at least one usage attribute, providing a computational inference model, generated from a plurality of brain activity data sets and a plurality of usage data sets, wherein each brain activity data set comprises data derived from a brain activity response following a sensory stimulus, submitting the attribute data of each of the at least one usage attributes to said computational inference model, estimating a brain activity response following a sensory stimulus of said person by evaluating said computational inference model for the submitted attribute data. The method is useful to determine, for example the influence of intensive touch pad usage (of a smartphone) on somatosensory evoked potentials.

Abstract: According to one embodiment, there is provided herein a system and method for producing a well lifecycle lift plan that includes considerations of multiple types of lift, multiple lift configurations associated with each lift type, and can be used to provide a prediction of when or if it would be desirable to change the lift plan at some time in the future. Another embodiment utilizes a heuristic database with rules that might be used to limit the solution space in some instances by restricting the solution to feasible configurations. A further embodiment teaches how multiple individual well optimization results might be combined with a reservoir model to obtain an optimized lift schedule for an entire field.

Abstract: An embodiment for a computing device is described herein. The computing device may include a word database enhancer, a recommendation engine, a keyboard monitor, a ranking and display manager, and a keyboard. The keyboard may be a configurable physical keyboard device that includes an embedded display, where the embedded display is a runtime configurable display. The keyboard may display configurable images in the form of auto-text completion text or a decrypted password. The keyboard may also include a microcontroller, a touch sensor, and a keyboard filter driver.

Abstract: An electronic appropriateness assessment tool (“tool”) can be configured to select information in response to an electronic request for the information. In one example, the request may be by a device associated with a user. In another example request may be by a social media platform. Before providing the information to the device, the tool can determine an appropriateness level of the information. In some instances, the tool can determine the appropriateness level based on social media data. The social media data may be expressions of sentiment about content made by social contacts of the user via the social media platform. The electronic appropriateness assessment tool can further determine a degree of the information to provide for presentation based on the appropriateness level.

Abstract: A question database storing questions and a conditional probability of one question to be asked given that a previous question was asked is searched to predict a future question based on the conditional probability stored in the question database given an input question as the previous question. The future question is suggested to a user. Responsive to receiving an acceptance of the future question, the question database is updated to strengthen the conditional probability associated with the future question occurring given the input question. An answer to the future question is provided and searching, predicting, suggesting and updating may be repeated, with the future question as the input question, until the future question is declined.

Abstract: A method for estimating confidence bounds for adjusted rainfall values for a set of geo-locations using agricultural data comprises using a server computer system that receives, via a network, agricultural data records that are used to estimate rainfall values for the set of geo-locations. Within the server computer system, rainfall calculation instructions receive digital data including observed radar and rain-gauge agricultural data records. The computer system then aggregates the agricultural data records and creates and stores the agricultural data sets. The agricultural data records are then used to estimate adjusted rainfall values for a set of geo-locations. Rainfall confidence bounds instructions estimate a set of confidence bounds for each of the adjusted rainfall values for the set of geo-locations. The set of confidence bounds provide a range for each of the adjusted rainfall values that represents a particular level of confidence associated with each of the adjusted rainfall values.

Abstract: The disclosed embodiments relate to a system that reduces bandwidth requirements for transmitting telemetry data from sensors in a computer system. During operation, the system obtains a cross-imputability value for each sensor in a set of sensors that are monitoring the computer system, wherein a cross-imputability value for a sensor indicates how well a sensor value obtained from the sensor can be predicted based on sensor values obtained from other sensors in the set. Next, the system clusters sensors in the set of sensors into two or more groups based on the determined cross-imputability values. Then, while transmitting sensor values from the set of sensors, for a group of sensors having cross-imputability values exceeding a threshold, the system selectively transmits sensor values from some but not all of the sensors in the group to reduce a number of sensor values transmitted.

Abstract: Various systems, mediums, and methods for providing services may involve data engines configured to generate scores associated with one or more entities and then to classify the entities based on the scores. The data engine may collect data and based on the collected data may generate a first behavior model in a first time span, and a second and third behavior models in a second time span. The data engine may generate a first score based on the first behavior model, a second score based on the second behavior model, and a third score based on the third behavior model. The data engine may generate a final score based on the first, second, and third scores. The data engine can classify the entity based on the final score. The data engine can then automatically adjust one of the services provided to the entity based on the final score.

Abstract: Methods and systems are provided for condition-based maintenance of a structural component exhibiting a physical defect. One exemplary system comprises a measurement system to obtain a current measurement of a defect in a structure, a monitoring system, and a maintenance system. The monitoring system determines a probabilistic representation of degradation development data for the defect using the current measurement, determines a reference remaining usage life metric for the structure based on the probabilistic representation and a target probability value, and determines one or more remaining usage life bounds based at least in part on the reference remaining usage life metric. The maintenance system determines maintenance schedule or other remedial action(s) for the structure in a manner that is influenced by the reference remaining usage life metric and the one or more remaining usage life bounds.