Abstract: An example method includes obtaining an image of a lead implanted in a patient, the lead including one or more electrodes positioned along a longitudinal axis of the lead and a plurality of orientation markers; determining, in the image, respective locations of the electrodes and respective locations of the orientation markers; obtaining a template model corresponding to the lead; determining a transform between the determined locations of the one or more electrodes and the plurality of orientation markers and locations of corresponding electrodes and orientation markers in the template model; and determining the rotational orientation of the lead based on the transform.

Abstract: An object tracking system includes a sensor and a tracking system. The sensor is configured to capture a frame of at least a portion of a physical space within a global plane for a space. The tracking system is configured to receive the frame, to detect an object within a zone of the frame, and to determine a pixel location for the object. The tracking system is further configured to identify a zone of the physical structure based on the pixel location, to identify an item based on the identified zone.

Abstract: Systems and methods are disclosed for correcting for artificial deformations in anatomical modeling. One method includes obtaining an anatomic model; obtaining information indicating a presence of an artificial deformation of the anatomic model; identifying a portion of the anatomic model associated with the artificial deformation; estimating a non-deformed local area corresponding to the portion of the anatomic model; and modifying the portion of the anatomic model associated with the artificial deformation, based on the estimated non-deformed local area.

Abstract: The system and method for biometric safe blood donor certification and geo-location system provides a safe blood donor biometric certification and geolocation tracking system that is an efficient, accurate, and portable device to acquire biometric data to authenticate identity of an individual and link the biometric identity to the blood test samples and results. This technology can unequivocally identify the person with their blood profile. The technology can track location of potential donor individuals with geo-location Global Positioning Satellite sensors and alert these individuals when a nearby patient requests their blood type. All eligible blood donors can be alerted about the opportunity to respond and accept the invitation for blood donation. Those who donate blood are removed from the eligibility list until they can safely donate again. This system eliminates the need for complex equipment and facilities to store donated blood for extended periods and eliminates waste of unused blood.

Abstract: A palm vein identification apparatus includes a base to support a first sensor; the first sensor mounted on the base via a multi-axis gimbal, the multi-axis gimbal to provide movement of the sensor such that the sensor can capture one or more images from a plurality of angles; a position control in communication with the first sensor and to correct movement of the first sensor; and a secondary sensor mounted on the base, the secondary sensor to capture an environment around the palm vein identification apparatus to detect a palm; the first sensor is positioned based on information collected from the secondary sensor.

Abstract: A method of generating a training data set for training an image matting machine learning model includes receiving a plurality of foreground images, generating a plurality of composited foreground images by compositing randomly selected foreground images from the plurality of foreground images, and generating a plurality of training images by compositing each composited foreground image with a randomly selected background image. The training data set includes the plurality of training images.

Abstract: Computer-implemented method for transferring style features from at least one source image to a target image, comprising the steps of generating a result image, based on the source and the target image, wherein one or more spatially-variant features of the result image correspond to one or more spatially variant features of the target image; and wherein a texture of the result image corresponds to a texture of the source image; and outputting the result image, and a corresponding device. According to the invention, the texture corresponds to a summary statistic of spatially variant features of the source image.

Abstract: Methods and apparatus for using features of images representing content items to improve the presentation of the content items are disclosed. In one embodiment, a plurality of digital images are obtained, where each of the images represents a corresponding one of a plurality of content items Image features of each of the digital images are determined. Additional features including at least one of user features pertaining to a user of a client device or contextual features pertaining to the client device are ascertained. At least a portion of the content items are provided via a network to the client device using features that include or are derived from both the image features of each of the plurality of digital images and the additional features.

Abstract: A system for decoding a barcode based on gesture detection and analysis is disclosed herein. The system may receive an image stream of an environment. The system may determine, based on processing images of the image stream, a gesture region of the image stream. The system may detect a gesture, by a user, based on analyzing the gesture region. The system may determine a barcode region of the image stream based on a position of the user when performing the gesture. The system may identify a barcode in the environment based on analyzing the barcode region. The system may decode the barcode based on a format of the barcode.

Abstract: Methods, systems, and storage media for classifying content across media formats based on weak supervision and cross-modal training are disclosed. The system can maintain a first feature classifier and a second feature classifier that classifies features of content having a first and second media format, respectively. The system can extract a feature space from a content item using the first feature classifier and the second feature classifier. The system can apply a set of content rules to the feature space to determine content metrics. The system can correlate a set of known labelled data to the feature space to construct determinative training data. The system can train a discrimination model using the content item and the determinative training data. The system can classify content using the discrimination model to assign a content policy to the second content item.

Abstract: Embodiments relate to a system, program product, and method for inducing creativity in an artificial neural network (ANN) having an encoder and decoder. Neurons are automatically selected and manipulated from one or more layers of the encoder. An encoded vector is sampled for an encoded image. Decoder neurons and a corresponding activation pattern are evaluated with respect to the encoded image. The decoder neurons that correspond to the activation pattern are selected, and an activation setting of the selected decoder neurons is changed. One or more novel data instances are automatically generated from an original latent space of the selectively changed decoder neurons.

Abstract: Techniques are generally described for generation of photorealistic synthetic image data. A generator network generates first synthetic image data. A first class of image data represented by a first portion of the first synthetic image data is detected and the first portion is sent to a first discriminator network. The first discriminator network generates a prediction of whether the first portion of the first synthetic image data is synthetically generated. A second class of image data represented by a second portion of the first synthetic image data is detected and the second portion is sent to a second discriminator network. The second discriminator network generates a prediction of whether the second portion of the first synthetic image data is synthetically generated. The generator network is updated based on the predictions of the discriminators.

Abstract: Smart sensor methods and systems are described that improve on prior systems. An example device includes a sensor, a memory, a network connection, and two processing units, wherein a first processing unit compares current data provided by the first sensor to the reference data previously provided by the first sensor. Based on the result of the comparison, a second processing unit may be enabled to process the current data, or may be disabled to prevent the second processing unit from processing the current data.

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: The disclosed embodiments provide systems and methods for predicting presence of one or more neurological deficits. The system may include a microphone, a camera, one or more memory devices storing instructions, and one or more processors configured to execute the instructions to extract audio information including a period density entropy coefficient and a mel frequency cepstral coefficient from an audio feed received from the microphone. Additionally, the instructions may cause the processor to determine position and depth information of eye movement from a video feed received from the camera and detect features of interest including facial landmarks, spatial orientation of limbs, and positional information of limb movements from the video feed. The one or more processors may further extract the features of interest from the video feed and process the extracted features of interest by aligning the extracted features of interest to a common reference.

Abstract: A method of characterizing a serum and plasma portion of a specimen in regions occluded by one or more labels. The characterization method may be used to provide input to an HILN (H, I, and/or L, or N) detection method. The characterization method includes capturing one or more images of a labeled specimen container including a serum or plasma portion from multiple viewpoints, processing the one or more images to provide segmentation data including identification of a label-containing region, determining a closest label match of the label-containing region to a reference label configuration selected from a reference label configuration database, and generating a combined representation based on the segmentation information and the closest label match. Using the combined representation allows for compensation of the light blocking effects of the label-containing region. Quality check modules and testing apparatus and adapted to carry out the method are described, as are other aspects.

Abstract: A method and apparatus with fingerprint verification are disclosed. A processor implemented method includes obtaining a query fingerprint image through a fingerprint sensor, obtaining a processed fingerprint image by performing image processing on the obtained query fingerprint image, obtaining a blended fingerprint image by blending the query fingerprint image and the processed fingerprint image, and performing fingerprint verification based on the blended fingerprint image and a registered fingerprint image.

Abstract: The disclosure features systems and methods for measuring and diagnosing target constituents bound to labeling particles in a sample. The systems include a radiation source, a sample holder, a detector configured to obtain one or more diffraction patterns of the sample each including information corresponding to optical properties of sample constituents, and an electronic processor configured to, for each of the one or more diffraction patterns: (a) analyze the diffraction pattern to obtain amplitude information and phase information corresponding to the sample constituents; (b) identify one or more particle-bound target sample constituents based on at least one of the amplitude information and the phase information; and (c) determine an amount of at least one of the particle-bound target sample constituents in the sample based on at least one of the amplitude information and the phase information.

Abstract: Methods, systems, and non-transitory computer readable storage media are disclosed for generating a machine-learning model and encoding ownership information in the machine-learning model. For example, the disclosed system can generate parameters of a machine-learning model utilizing digital content items modified by a filter. The disclosed system can then process digital content items modified by the filter to generate first outputs based on the digital content items being modified by the filter. The disclosed system can also process digital content items unmodified by the filter to generate second outputs based on the digital content items not being modified by the filter. The disclosed system can determine that the second outputs are degraded relative to the first outputs. Accordingly, the disclosed system can determine ownership of the machine-learning model based on detecting that information about the filter is embedded in parameters of the machine-learning model.

Abstract: A machine-implemented method for automated detection of drowsiness, which includes receiving from an imaging device directed at the face of an operator a series of images of the face of the operator onto processing hardware, on the processor detecting facial landmarks of the operator from the series of images to determine the level of talking by the operator, the level of yawning of the operator, the PERCLOS of the operator, on the processor detecting the facial pose of the operator from the series of images to determine the level of gaze fixation by the operator, on the processor calculating the level of drowsiness of the operator by ensembling the level of talking by the operator, the level of yawning of the operator, the PERCLOS of the operator and the level of gaze fixation by the operator, and generating an alarm when the calculated level of drowsiness of the operator exceeds a predefined value.