Abstract: Estimating a three-dimensional (3D) pose and shape of an articulated body mesh is useful for many different applications including health and fitness, entertainment, and computer graphics. A set of estimated 3D keypoint positions for a human body structure are processed to compute parameters defining the pose and shape of a parametric human body mesh using a set of geometric operations. During processing, 3D keypoints are extracted from the parametric human body mesh and a set of rotations are computed to align the extracted 3D keypoints with the estimated 3D keypoints. The set of rotations may correctly position a particular 3D keypoint location at a “joint”, but an arbitrary number of rotations of the “joint” keypoint may produce a twist in a connection to a child keypoint. Rules are applied to the set of rotations to resolve ambiguous twists and articulate the parametric human body mesh according to the computed parameters.

Abstract: Apparatuses, systems, and techniques for calculating data compression parameters using codebook entry values. In at least one embodiment, one or more circuits is to calculate one or more data compression parameters based, at least in part, on at least on one or more values of the data to be compressed in relation to at least two codebook entry values.

Abstract: A method, computer readable medium, and system are disclosed for neural network pruning. The method includes the steps of receiving first-order gradients of a cost function relative to layer parameters for a trained neural network and computing a pruning criterion for each layer parameter based on the first-order gradient corresponding to the layer parameter, where the pruning criterion indicates an importance of each neuron that is included in the trained neural network and is associated with the layer parameter. The method includes the additional steps of identifying at least one neuron having a lowest importance and removing the at least one neuron from the trained neural network to produce a pruned neural network.

Abstract: Apparatuses, systems, and techniques to reduce a size of neural networks. In at least one embodiment, a size of a neural network is reduced by at least removing one or more neurons of the neural network and adjusting one or more layers of the neural network to compensate for the removed one or more neurons.

Abstract: The Bone Dust Trap for collecting bone dust during various surgical procedures for subsequent bone graft implantation. The device includes cylindrical housing unit covered with the lid, attached to the central pipe with the porous tip. The pipe connects the cyclone forming mechanism and filtrating membrane, located at the lower part of the central pipe. The membrane interlinks with the plurality of porous plates located along the walls of the cylinder. The cyclone forming mechanism, consisting of the inlet port with conical jet and the spiral helix, creates spiral movement of the incoming fluid. The liquid is further directed towards the 2-stage filtrating system with the said porous plates, where larger bone particles are accumulated, and then to the filtrating membrane, which collects smaller particles. The fluid is extracted through the central pipe. The lid can be removed to collect the bone particles from plates and membrane.

Abstract: The proposed method and device relate to acousto-optics and laser technology and can be attributed, in particular, to acousto-optical (AO) laser resonator Q-switches, AO devices for extra-cavity control of single-mode (collimated) and multimode (uncollimated) monochromatic and non-monochromatic laser radiation, i.e, AO modulators, AO frequency shifters, and dispersion delay lines for visible and middle IR wavelengths (0.4-5.5 ?m). The object of the method and device is providing a geometry of AO interaction in laser resonator Q-switches so that to optimize the preset parameters of the Q-switch in accordance with the system requirements to the laser operation mode depending on the intended use of the laser, more specifically, lower control RF power and capability of operation without additional efficiency loss with multimode or uncollimated laser radiation.

Abstract: Various embodiments enable a robot, or other autonomous or semi-autonomous device or system, to receive data involving the performance of a task in the physical world. The data can be provided as input to a perception network to infer a set of percepts about the task, which can correspond to relationships between objects observed during the performance. The percepts can be provided as input to a plan generation network, which can infer a set of actions as part of a plan. Each action can correspond to one of the observed relationships. The plan can be reviewed and any corrections made, either manually or through another demonstration of the task. Once the plan is verified as correct, the plan (and any related data) can be provided as input to an execution network that can infer instructions to cause the robot, and/or another robot, to perform the task.

Abstract: An application using a VPN is programmed to transmit proxy traffic to a remote proxy server. Traffic to the proxy server is intercepted, shifted to user space, and processed according to one or more options. Traffic may be terminated by a local proxy that resolves domain names in traffic and requests referenced content. Intercepted traffic may include plain text data in headers that is encrypted before forwarding to a different proxy server. Traffic may be evaluated, such as a User Agent string in order to determine routing choices, such as blocking, throttling, local termination, transmitting through a VPN, or other options. Multiple VPNs may operate on the same user computer and proxy traffic may be intercepted and processed by transmitting it through a VPN, bypassing all VPNs, or routing through a different VPN.

Abstract: An apparatus pulls a single crystal of semiconductor material by the Czochralski (CZ) method from a melt. The apparatus includes: a crucible that accommodates the melt; a resistance heater around the crucible; a camera system for observing a phase boundary between the melt and a growing single crystal, the camera system having an optical axis; a heat shield in frustoconical form with a narrowing diameter in a region at its lower end and arranged above the crucible and surrounding the growing single crystal; and an annular element, which is configured to capture particles, that projects inward from an inner side face of the heat shield and has an arrestor edge directed upward at an inner end of the annular element. The optical axis of the camera system runs between the arrestor edge and the growing single crystal. The annular element is releasably connected to the heat shield.

Abstract: An apparatus is configured to create a logging template comprising instructions for managing logging of scripts executed from a front-end and implemented in a back-end of an information technology workflow orchestration system. The apparatus is also configured to provide the logging template in a catalog of application programming interfaces in a user interface of the front-end enabling selection of instructions from the logging template for inclusion in scripts generated in the front-end. The processing device is further configured to generate a given script by selecting, utilizing the user interface, a set of elements from the catalog including one or more instructions from the logging template. The processing device is further configured to execute the given script in the front-end utilizing at least one of the instructions from the logging template to view, in the user interface of the front-end, logs produced by the back-end in response to the given script.

Abstract: A method of generating a weather forecast. The method is executable by a server, the server including a processor, the processor configured to execute a Machine Learning Algorithm (MLA). The method comprises: receiving, by the MLA at the given period of time, satellite data for a given geographical region; based on the satellite data, generating by the MLA, a 3D precipitation map for the given geographical region, based on the 3D precipitation map, generating by the MLA the weather forecast for the given period of time for the given geographical region. The MLA is trained based on a prediction of another MLA (based on meteo radar data) and satellite data.

Abstract: A method, computer readable medium, and system are disclosed for visual sequence learning using neural networks. The method includes the steps of replacing a non-recurrent layer within a trained convolutional neural network model with a recurrent layer to produce a visual sequence learning neural network model and transforming feedforward weights for the non-recurrent layer into input-to-hidden weights of the recurrent layer to produce a transformed recurrent layer. The method also includes the steps of setting hidden-to-hidden weights of the recurrent layer to initial values and processing video image data by the visual sequence learning neural network model to generate classification or regression output data.

Abstract: Learning to estimate a 3D body pose, and likewise the pose of any type of object, from a single 2D image is of great interest for many practical graphics applications and generally relies on neural networks that have been trained with sample data which annotates (labels) each sample 2D image with a known 3D pose. Requiring this labeled training data however has various drawbacks, including for example that traditionally used training data sets lack diversity and therefore limit the extent to which neural networks are able to estimate 3D pose. Expanding these training data sets is also difficult since it requires manually provided annotations for 2D images, which is time consuming and prone to errors. The present disclosure overcomes these and other limitations of existing techniques by providing a model that is trained from unlabeled multi-view data for use in 3D pose estimation.

Abstract: An application using a virtual private network (VPN) is programmed to transmit proxy traffic to a remote proxy server. Traffic to the proxy server is intercepted, shifted to user space, and processed according to one or more options. Traffic may be terminated by a local proxy that resolves domain names in traffic and requests referenced content. Intercepted traffic may include plain text data in headers that is encrypted before forwarding to a different proxy server. Traffic may be evaluated, such as a User Agent string in order to determine routing choices, such as blocking, throttling, local termination, transmitting through a VPN, or other options. Multiple VPNs may operate on the same user computer and proxy traffic may be intercepted and processed by transmitting it through a VPN, bypassing all VPNs, or routing through a different VPN.

Abstract: Apparatuses, systems, and techniques that determine the pose of a human hand from a 2-D image are described herein. In at least one embodiment, training of a neural network is augmented using weakly labeled or unlabeled pose data which is augmented with losses based on a human hand model.

Abstract: An apparatus is configured to create a logging template comprising instructions for managing logging of scripts executed from a front-end and implemented in a back-end of an information technology workflow orchestration system. The apparatus is also configured to provide the logging template in a catalog of application programming interfaces in a user interface of the front-end enabling selection of instructions from the logging template for inclusion in scripts generated in the front-end. The processing device is further configured to generate a given script by selecting, utilizing the user interface, a set of elements from the catalog including one or more instructions from the logging template. The processing device is further configured to execute the given script in the front-end utilizing at least one of the instructions from the logging template to view, in the user interface of the front-end, logs produced by the back-end in response to the given script.

Abstract: A method, computer readable medium, and system are disclosed for visual sequence learning using neural networks. The method includes the steps of replacing a non-recurrent layer within a trained convolutional neural network model with a recurrent layer to produce a visual sequence learning neural network model and transforming feedforward weights for the non-recurrent layer into input-to-hidden weights of the recurrent layer to produce a transformed recurrent layer. The method also includes the steps of setting hidden-to-hidden weights of the recurrent layer to initial values and processing video image data by the visual sequence learning neural network model to generate classification or regression output data.

Abstract: Systems and methods for more accurate and robust determination of subject characteristics from an image of the subject. One or more machine learning models receive as input an image of a subject, and output both facial landmarks and associated confidence values. Confidence values represent the degrees to which portions of the subject's face corresponding to those landmarks are occluded, i.e., the amount of uncertainty in the position of each landmark location. These landmark points and their associated confidence values, and/or associated information, may then be input to another set of one or more machine learning models which may output any facial analysis quantity or quantities, such as the subject's gaze direction, head pose, drowsiness state, cognitive load, or distraction state.

Abstract: Apparatuses, systems, and techniques are presented to generate data useful for further training of a neural network. In at least one embodiment, one or more neural networks can be re-trained based, at least in part, on data generated by the one or more neural networks including data used to previously train the one or more neural networks.

Abstract: Estimating a three-dimensional (3D) pose of an object, such as a hand or body (human, animal, robot, etc.), from a 2D image is necessary for human-computer interaction. A hand pose can be represented by a set of points in 3D space, called keypoints. Two coordinates (x,y) represent spatial displacement and a third coordinate represents a depth of every point with respect to the camera. A monocular camera is used to capture an image of the 3D pose, but does not capture depth information. A neural network architecture is configured to generate a depth value for each keypoint in the captured image, even when portions of the pose are occluded, or the orientation of the object is ambiguous. Generation of the depth values enables estimation of the 3D pose of the object.