Abstract: Provided herein are a calibration method for a fingerprint sensor and a display device using the calibration method, where, in the calibration method for a fingerprint sensor, the fingerprint sensor includes a substrate, a light-blocking layer located on a first surface of the substrate and having openings formed in a light-blocking mask, a light-emitting element layer located on the light-blocking layer and having a plurality of light-emitting elements, and a sensor layer located on a second surface of the substrate and having a plurality of photosensors; and the calibration method includes generating calibration data through white calibration and dark calibration, and applying offsets to the plurality of photosensors using the calibration data.

Abstract: A server acquires a feature label vector of each seed user and forms a first number of clusters corresponding different information categories according to the feature label vectors of the seed users. The server calculates a central vector of each cluster according to the feature label vectors of the seed users in the cluster. The server acquires a feature weight vector corresponding to the information categories. The server acquires a feature label vector of each potential user. The server calculates first distances from the potential users to the central vector of the information categories according to the feature label vectors of the potential users, feature weight vectors and central vectors corresponding to the information categories. The server selects a second number of potential users corresponding to the shortest first distances from the first distances and sends them information that is matched with corresponding information categories of the target users.

Abstract: Embodiments of the present application disclose a fingerprint identification apparatus and an electronic device. The fingerprint identification apparatus is used to be disposed under a display screen and includes a first filter layer and a fingerprint sensor, and the first filter layer is disposed above the fingerprint sensor, the first filter layer includes a plurality of first filter units, and the plurality of first filter units are disposed in a region of the first filter layer corresponding to an edge region of the fingerprint sensor; sensing units of the edge region of the fingerprint sensor are configured to receive a light signal returned by a finger above the display screen and filtered by the plurality of first filter units; and sensing units of a middle region of the fingerprint sensor are configured to receive a light signal returned by the finger, to generate a fingerprint image of the finger.

Abstract: The present disclosure provides a texture detection module, a method for driving the same and a display device. The texture detection module includes: an emission electrode layer; a receiver electrode layer; and a piezoelectric film between the emission electrode layer and the receiver electrode layer. The emission electrode layer includes emission electrodes, first emission signal lines and second emission signal lines. The emission electrodes include first emission sub-electrodes and second emission sub-electrodes that are insulated from the first emission sub-electrodes. The first emission sub-electrodes are arranged in N rows and M columns, N and M are both positive integers; the first emission sub-electrodes located in an identical row are electrically coupled to one identical first emission signal line.

Abstract: A fingerprint sensor is provided and includes substrate; sensor electrodes on substrate; first switches coupled to sensor electrodes; organic layer covering sensor electrodes; control line drive circuit in first direction; signal line drive circuit in second direction orthogonal to first direction; signal lines coupled to first switches; control lines coupling first switches to control line drive circuit; sensor drive electrode surrounding sensor electrodes; second switches between signal line drive circuit and signal lines; and first number of third switches between signal line drive circuit and first number of second switches, wherein distance of sensor drive electrode from surface of substrate is larger than distance of sensor electrodes from surface of substrate, and wherein first number is less than number of all second switches.

Abstract: A method, system, and computer program product for visualizing a machine learning model are provided. A confusion matrix and model performance metric data are received from a classification model. For each data point in the confusion matrix, a corresponding pixel is generated. The pixels are grouped into clusters. Each cluster represents a label in the confusion matrix. A centroid is generated for each cluster. Using the model performance metric data, a misclassification indicator arrow is generated for each misclassified data point. The misclassification indicator arrow indicates both the predicted class and the actual class. The clusters, the centroids, and the misclassification indicator arrow are displayed as a graphical visualization of the machine learning model.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for characterizing a gaze position of a user in a query image. One of the methods includes obtaining a query image of a user captured by a camera of a mobile device; obtaining device characteristics data specifying (ii) characteristics of the mobile device, (ii) characteristics of the camera of the mobile device, or (iii) both; and processing a neural network input comprising (i) one or more images derived from the query image and (ii) the device characteristics data using a gaze prediction neural network, wherein the gaze prediction neural network is configured to, at run time and after the gaze prediction neural network has been trained, process the neural network input to generate a neural network output that characterizes a gaze position of the user in the query image.

Abstract: Methods and systems to synthesize information from multiple discrete and unrelated documents, and from the synthesized information verify the identity of an individual to a high degree of trust are described. Information is adaptively synthesized from varied documents, and through generation of document confidence scores. Enrollment requirements for a trusted identification are evaluated in a real-time environment. The enrollment requirements may represent a minimum level of documentation required to sufficiently verify an individual's true identity in order to permit issuance of the trusted identification. Once sufficient documentation has been obtained and validated to meet or exceed enrollment requirements, the documentation (including any original source copies of any documentation) is securely submitted to the trusted identification issuing authority.

Abstract: Biometric gallery management is performed by association one or more wireless identifiers that correspond to one or more mobile devices (such as smart phones, tablet computing devices, cellular telephones, wearable devices, smart watches, fitness monitors, digital media players, medical devices, and/or other mobile computing devices) that people carry with digital representations of biometrics corresponding to the people. Wireless identifiers corresponding to mobile devices proximate to a biometric reader device may be monitored. Upon detection of wireless identifiers corresponding to mobile devices proximate to the biometric reader device, the associated digital representations of biometrics may be loaded from a main gallery into one or more local galleries, which may then be used to perform one or more biometric identifications and/or verifications.

Abstract: The present disclosure relates to systems and methods for analyzing and evaluating movement of a subjects and providing feedback. In some embodiments, a method comprises receiving one or more images of a body of the subject captured during performance of a physical movement by the subject; computing a model descriptive of positions and orientations of body parts of the subject based on the one or more images; generating a comparison of the positions and orientations to target positions and target orientations, respectively, for the physical movement; and generating a recommendation based on the comparison.

Abstract: Techniques are disclosed for providing a notification that a person is at a particular location. For example, a resident device may receive from a user device an image that shows a face of a first person, the image being captured by a first camera of the user device. The resident device may also receive, from another device having a second camera, a second image showing a portion of a face of a second person, the second camera having a viewable area showing a particular location. The resident device may determine a score indicating a level of similarity between a first set of characteristics associated with the face of the first person and a second set of characteristics associated with the face of a second person. The resident device may then provide to the user device a notification based on determining the score.

Abstract: Systems, apparatuses and methods may store a plurality of classes that represent a plurality of clusters in a cache. Each of the classes represents a group of the plurality of clusters and the plurality of clusters is in a first data format. The systems, apparatuses and methods further modify input data from a second data format to the first data format and conduct a similarity search based on the input data in the first data format to assign the input data to at least one class of the classes.

Abstract: The present disclosure provides a method for facilitating implementing biometric recognition. Further, the method may include receiving two or more biometric images of one or more biometric identifiers of one or more individuals from one or more devices. Further, the two or more biometric images may be in two or more spectrums. Further, the method may include analyzing the two or more biometric images using one or more deep hashing network models. Further, the method may include extracting two or more discriminative deep hashing codes from the two or more biometric images based on the analyzing. Further, the method may include generating a biometric template based on the two or more discriminative deep hashing codes. Further, the method may include generating a biometric key for the one or more biometric identifiers using a fuzzy commitment scheme based on the biometric template. Further, the method may include storing the biometric key.

Abstract: An in-vehicle information system mounted on a vehicle is provided. The system comprises a registration unit configured to register identification information and a name of each user and a name of a group including a plurality of users; a recognition unit configured to recognize a user who is an occupant of the vehicle based on the identification information; and a control unit configured to cause an output unit to output a name corresponding to the user recognized by the recognition means.

Abstract: Implementations of the present disclosure include receiving a color image and an IR image, the IR image taken contemporaneously with the color image, providing a set of facial landmarks depicted in the color image, determining a depth value for each facial landmark in the set of color landmarks, depth values being provided from the IR image, determining an average depth difference based on at least a sub-set of facial landmarks in the set of facial landmarks, comparing the average depth difference to a difference threshold to provide a comparison, and selectively authenticating the person based on the comparison.

Abstract: In an illustrative embodiment, systems and methods for assisting users in identifying unknown individuals in photographs first apply facial recognition to obtain a first likelihood of match between a target face and other faces in a corpus of images provided by users of a genealogy platform, and then adjusts the first likelihood of match according to similarities and dissimilarities in attributes supplied by users regarding individuals represented by each face. Resultant likelihoods drive presentation of potential matches for consideration by a requesting user.

Abstract: A method for determining population density of a defined space from multi-camera sourced imagery includes loading a set of images acquired from multiple different cameras positioned about the defined space, locating different individuals within each of the images and computing a population distribution of the located different individuals in respect to different locations of the defined space. The method additionally includes submitting each of the images to a convolutional neural network as training data, each in association with a correspondingly computed population distribution. Subsequent to the submission, contemporaneous imagery from the different cameras is acquired in real time and submitted to the neural network, in response to which, a predicted population distribution for the defined space is received from the neural network. Finally, a message is displayed that includes information correlating at least a portion of the population distribution with a specific location of the defined space.

Abstract: Disclosed is an electronic device that includes a housing, a display module that includes a first panel including a first surface, a second surface opposite to the first surface, and a plurality of pixels disposed between the first surface and the second surface, a cover layer that is disposed on the first surface of the first panel and that forms one surface of the housing, and a second panel disposed on the second surface of the first panel, and a sensor that is coupled to the display module and that forms a sensing area on the one surface of the housing. The display module includes an opening that is formed through the second panel and in which the sensor is disposed, and the sensor includes an active area and an inactive area formed around the active area. A first adhesive material is formed between the active area and the first panel. The first adhesive material includes a mechanical or thermal characteristic that a glass transition temperature Tg ranges from 0° C. to 25° C.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for image processing using deep neural networks. One of the methods includes receiving data characterizing an input image; processing the data characterizing the input image using a deep neural network to generate an alternative representation of the input image, wherein the deep neural network comprises a plurality of subnetworks, wherein the subnetworks are arranged in a sequence from lowest to highest, and wherein processing the data characterizing the input image using the deep neural network comprises processing the data through each of the subnetworks in the sequence; and processing the alternative representation of the input image through an output layer to generate an output from the input image.

Abstract: A method for performing searches of user information comprises: receiving an initial dataset including the user information; calculating distance metrics between pairs of data in the initial dataset; performing unsupervised learning on the initial dataset to obtain a plurality of total number of clusters, each total number of clusters covering the initial dataset; determining efficacy measures for each total number of clusters using a plurality of distance metric thresholds; determining a desired efficacy measure in the efficacy measures, the desired efficacy measure corresponding to a desired distance metric threshold in the plurality of distance metric thresholds; determining a desired total number of clusters in the plurality of total number of clusters, the desired total number of clusters corresponding to the desired distance metric threshold; and performing unsupervised learning on the initial dataset using the desired total number of clusters to obtain a number of data representations of the user infor