Abstract: Techniques for determining print quality for a 3D printer are disclosed. An example method includes obtaining an image of a stream of material jetted from a nozzle of the 3D printer, and binarizing the image to distinguish background features from foreground features contained in the image. The method also includes identifying elements of jetted material in the foreground features, and computing statistical data characterizing the identified elements. The method also includes generating a quality score of jetting quality based on the statistical data and controlling the 3D printer based on the quality score. The quality score indicates a degree to which the elements of jetted material form droplets of a same size, shape, alignment, and jetting frequency.

Abstract: Systems and methods may use a mobile device communicatively coupled to a wearable device to present an exercise to a user. The systems and methods may modify a therapy calendar, for example, based on information determined from the exercise (e.g., repetitions completed, a duration completed, video, etc.), feedback from the user, or the like. A method may include receiving a control command from a wearable device communicatively coupled to a mobile device, the control command causing an action to be taken by the mobile device related to the exercise. The therapy calendar may be automatically modified, such as in response to determining a number of repetitions or a duration of an exercise. The modified therapy calendar may be presented on a user interface, such as on a display of the wearable device or the mobile device.

Abstract: A space based multi-band GPS/GNSS navigation system, including: RF card to receive and process the two different received navigation signals; a space grade navigation processor configured to: execute processor instructions to process the two different received navigation signals to produce position, velocity, and time information; and process measurements using a Kalman filter for enhanced performance at high altitude.

Abstract: Systems and methods are provided for compressing and decompressing data in an ultrasound beamformer. The systems and methods include an encoder for compressing delay data based at least in part on a smoothness of a delay profile, and for compressing apodization data based at least in part on a smoothness of an apodization profile.

Abstract: A method of labeling training data includes inputting a plurality of unlabeled input data samples into each of a plurality of pre-trained neural networks and extracting a set of feature embeddings from multiple layer depths of each of the plurality of pre-trained neural networks. The method also includes generating a plurality of clusterings from the set of feature embeddings. The method also includes analyzing, by a processing device, the plurality of clusterings to identify a subset of the plurality of unlabeled input data samples that belong to a same unknown class. The method also includes assigning pseudo-labels to the subset of the plurality of unlabeled input data samples.

Abstract: A system and method for robust estimation of state parameters from internal readings in a sequence of images are provided. Various techniques can be implemented to address observation noise and/or underlying process noise to stabilize the readings.

Abstract: Provided is small arms ammunition projectile (24) and manufacturing method having a core (10) with a longitudinal core axis, a forward portion (18), and a rearward end (14). The core (10) has a rear portion (16) with an edge (26) that may be chamfered or radiused, a first portion (28) being frustoconical, and a second portion (30) adjacent the first portion (28) being substantially cylindrical. The jacket (12) has a longitudinal axis (99) and longitudinally extending socket (45) to receive the rear portion (16) of the core (10). The socket (45) has a socket bottom (46), a first socket portion (50) being frustoconical, and a second socket portion (52) adjacent the first socket portion (50) being substantially cylindrical.

Abstract: A system captures, by a recording device, a scene with physical objects, the scene displayed as a three-dimensional (3D) mesh. The system marks 3D annotations for a physical object and identifies a mask. The mask indicates background pixels corresponding to a region behind the physical object. Each background pixel is associated with a value. The system captures a plurality of images of the scene with varying features, wherein a respective image includes: two-dimensional (2D) projections corresponding to the marked 3D annotations for the physical object; and the mask based on the associated value for each background pixel. The system updates the value of each background pixel with a new value. The system trains a machine model using the respective image as generated labeled data, thereby obtaining the generated labeled data in an automated manner based on a minimal amount of marked annotations.

Abstract: A radio-frequency identification (RFID) fluid connection, including a tube or hose, the tube or hose including a radially outward facing surface, a RFID assembly or label connected the radially outward facing surface, including a RFID tag, and at least one contact electrically connected to the RFID tag.

Abstract: A method includes defining a model for a liquid while the liquid is positioned at least partially within a nozzle of a printer. The method also includes synthesizing video frames of the liquid using the model to produce synthetic video frames. The method also includes generating a labeled dataset that includes the synthetic video frames and corresponding model values. The method also includes receiving real video frames of the liquid while the liquid is positioned at least partially within the nozzle of the printer. The method also includes generating an inverse mapping from the real video frames to predicted model values using the labeled dataset. The method also includes reconstructing the liquid in the real video frames based at least partially upon the predicted model values.

Abstract: A method of labeling a dataset includes inputting a testing set comprising a plurality of input data samples into a plurality of pre-trained machine learning models to generate a set of embeddings output by the plurality of pre-trained machine learning models. The method further includes performing an iterative cluster labeling algorithm that includes generating a plurality of clusterings from the set of embeddings, analyzing the plurality of clusterings to identify a target embedding with a highest duster quality, analyzing the target embedding to determine a compactness for each of the plurality of clusterings of the target embedding, and identifying a target cluster among the plurality of clusterings of the target embedding based on the compactness. The method further includes assigning pseudo-labels to the subset of the plurality of input data samples that are members of the target duster.

Abstract: One embodiment provides a system that facilitates efficient collection of training data. During operation, the system obtains, by a recording device, a first image of a physical object in a scene which is associated with a three-dimensional (3D) world coordinate frame. The system marks, on the first image, a plurality of vertices associated with the physical object, wherein a vertex has 3D coordinates based on the 3D world coordinate frame. The system obtains a plurality of second images of the physical object in the scene while changing one or more characteristics of the scene. The system projects the marked vertices on to a respective second image to indicate a two-dimensional (2D) bounding area associated with the physical object.

Abstract: A decoder includes a feature extraction circuit for calculating one or more feature vectors. An acoustic model circuit is coupled to receive one or more feature vectors from and assign one or more likelihood values to the one or more feature vectors. A memory architecture that utilizes on-chip state lattices and an off-chip memory for storing states of transition of the decoder is used to reduce reading and writing to the off-chip memory. The on-chip state lattice is populated with at least one of the states of transition stored in the off-chip memory. An on-chip word is generated from a snapshot from the on-chip state lattice. The on-chip state lattice and the on-chip word lattice act as an on-chip cache to reduce reading and writing to the off-chip memory.

Abstract: A three-dimensional (3D) printer includes a nozzle and a camera configured to capture a real image or a real video of a liquid metal while the liquid metal is positioned at least partially within the nozzle. The 3D printer also includes a computing system configured to perform operations. The operations include generating a model of the liquid metal positioned at least partially within the nozzle. The operations also include generating a simulated image or a simulated video of the liquid metal positioned at least partially within the nozzle based at least partially upon the model. The operations also include generating a labeled dataset that comprises the simulated image or the simulated video and a first set of parameters. The operations also include reconstructing the liquid metal in the real image or the real video based at least partially upon the labeled dataset.

Abstract: A radio-frequency identification (RFID) fluid connection, including a tube or hose, the tube or hose including a radially outward facing surface, a RFID assembly or label connected the radially outward facing surface, including a RFID tag, and at least one contact electrically connected to the RFID tag.

Abstract: A system determines an input video and a first annotated image from the input video which identifies an object of interest. The system initiates a tracker based on the first annotated image and the input video. The tracker generates, based on the first annotated image and the input video, information including: a sliding window for false positives; a first set of unlabeled images from the input video; and at least two images with corresponding labeled states. A semi-supervised classifier classifies, based on the information, the first set of unlabeled images from the input video. If a first unlabeled image is classified as a false positive, the system reinitiates the tracker based on a second annotated image occurring in a frame prior to a frame with the false positive. The system generates an output video comprising the input video displayed with tracking on the object of interest.

Abstract: A radio-frequency identification (RFID) connector, including a connector, including at least one component, and a RFID assembly connected to the connector, the RFID assembly including a RFID tag, and at least one contact arranged on the at least one component and electrically connected to the RFID tag, wherein in an unlocked state of the RFID connector, the RFID tag indicates an open state of the RFID assembly, and in a locked state of the RFID connector, the RFID tag indicates a closed state of the RFID assembly.

Abstract: A system is provided which obtains images of a physical object captured by an AR recording device in a 3D scene. The system measures a level of diversity of the obtained images, for a respective image, based on at least: a distance and angle; a lighting condition; and a percentage of occlusion. The system generates, based on the level of diversity, a first visualization of additional images to be captured by projecting, on a display of the recording device, first instructions for capturing the additional images using the AR recording device. The system trains a model based on the collected data. The system performs an error analysis on the collected data to estimate an error rate for each image of the collected data. The system generates, based on the error analysis, a second visualization of further images to be captured. The model is further trained based on the collected data.

Abstract: A system and method provide extractions of regions of interest from images hand annotated by reviewers by lifting annotations from images, filtering out text labels, reconstructing continuous closed boundaries, and marking the contained region.

Abstract: A method and system are provided for an improved semantic segmentation using a multi-stream late fusion using pretrained encoders to encode disparate channels independently while also integrating selected image features at a more abstract level in order to provide improved localization and image classification.