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: 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.

Abstract: Detection of activity in video content, and more particularly detecting in video start and end frames inclusive of an activity and a classification for the activity, is fundamental for video analytics including categorizing, searching, indexing, segmentation, and retrieval of videos. Existing activity detection processes rely on a large set of features and classifiers that exhaustively run over every time step of a video at multiple temporal scales, or as a small improvement computationally propose segments of the video on which to perform classification. These existing activity detection processes, however, are computationally expensive, particularly when trying to achieve activity detection accuracy, and moreover are not configurable for any particular time or computation budget. The present disclosure provides a time and/or computation budget-aware method for detecting activity in video that relies on a recurrent neural network implementing a learned policy.

Abstract: A neural network is trained to identify one or more features of an image. The neural network is trained using a small number of original images, from which a plurality of additional images are derived. The additional images generated by rotating and decoding embeddings of the image in a latent space generated by an autoencoder. The images generated by the rotation and decoding exhibit changes to a feature that is in proportion to the amount of rotation.

Abstract: A virtual private router (VPR) intercepts DNS requests and returns a pseudo IP address to the requesting application and the pseudo IP address is mapped to a domain name in the request. Requests for content including the pseudo IP address are modified to include the corresponding domain name and transmitted to an intermediary server, which resolves the domain name to a real IP address and forwards the content request. The content is received by the intermediary server, which returns it to the requesting application, such as by way of the VPR. Real IP addresses may be returned by the intermediary server such that subsequent content requests to the domain name may bypass the intermediary server. Content requests may be sent to the intermediary server, which may instruct the VPR to bypass the server when bypass is needed.

Abstract: Systems and methods to detect one or more segments of one or more objects within one or more images based, at least in part, on a neural network trained in an unsupervised manner to infer the one or more segments. Systems and methods to help train one or more neural networks to detect one or more segments of one or more objects within one or more images in an unsupervised manner.

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 to generate coordinates of landmarks within images. The landmark locations may be identified on an image of a human face and used for emotion recognition, face identity verification, eye gaze tracking, pose estimation, etc. A transform is applied to input image data to produce transformed input image data. The transform is also applied to predicted coordinates for landmarks of the input image data to produce transformed predicted coordinates. A neural network model processes the transformed input image data to generate additional landmarks of the transformed input image data and additional predicted coordinates for each one of the additional landmarks. Parameters of the neural network model are updated to reduce differences between the transformed predicted coordinates and the additional predicted coordinates.

Abstract: A method, computer readable medium, and system are disclosed for sequential multi-tasking to generate coordinates of landmarks within images. The landmark locations may be identified on an image of a human face and used for emotion recognition, face identity verification, eye gaze tracking, pose estimation, etc. A neural network model processes input image data to generate pixel-level likelihood estimates for landmarks in the input image data and a soft-argmax function computes predicted coordinates of each landmark based on the pixel-level likelihood estimates.

Abstract: An approach is provided to process an image. The approach includes: obtaining a pixel shift set indicating information of movement of a plurality of pixels included in coinciding portions among a plurality of low-resolution images with respect to a single scene; dividing the pixel shift set into an integer portion and a fractional portion; generating an integer pixel shift set and a fractional pixel shift set; selecting a filter set corresponding to the plurality of pixels from among a plurality of pre-stored filter sets including a filter weight value applied to the pixels; and obtaining a high-resolution image with respect to the single scene, based on the plurality of low-resolution images, the selected filter set, and the integer pixel shift set.

Abstract: Some embodiments include a plasma source. The plasma source includes: (i) a plasma emitter having a first electrode and a second electrode defining an electrode gap therebetween; (ii) stands disposed adjacent to the electrode gap and the plasma emitter; (iii) emitter openings configured such that shockwaves generated by the plasma source are directed through the emitter openings and radially from the plasma emitter, wherein adjacent emitter openings of the emitter openings are separated from each other by at least one stand of the stands; (iv) an enclosure housing at a distal end of the plasma emitter and having a delivery device configured to introduce a conductor through an opening in the second electrode and into the electrode gap; and a device housing at a proximal end of the plasma emitter and having a transformer, a capacitor unit, and a contactor. Other embodiments of related systems and methods are also disclosed.

Abstract: A handshake message includes a field containing random data that is filled with data used to derive keying material on the source and destination computers. The data may be elliptic curve data and may include a representation of the data used by the destination computer to verify that elliptic curve data is present. The data may additionally include data for deriving second keying material on a second destination computer that the first destination computer forwards to the second computer, receives a response, and returns data from the response as part of its own handshake message.

Abstract: A handshake message includes a field containing random data that is filled with data used to derive keying material on the source and destination computers. The data may be elliptic curve data and may include a representation of the data used by the destination computer to verify that elliptic curve data is present. The data may additionally include data for deriving second keying material on a second destination computer that the first destination computer forwards to the second computer, receives a response, and returns data from the response as part of its own handshake message.

Abstract: A client and content provider are connected by a plurality of simultaneous transport connections. The number of the transport connections that are used to transfer data is selected based on the size of the data to be transferred and may change after transfer of data has commenced based on the amount of data left and the attributes of the transport connections. In another aspect, data to be transmitted over the transport connections is organized into frames such that each frame includes data from only one data stream. The frames are sized to be less than or equal to a control window of the transport connection over which they are transmitted. Each frame may be assigned to a transport connection in a round robin fashion or based on the size of the frame and the sizes of the control windows of the transport connections.

Abstract: A client and content provider are connected by a plurality of simultaneous transport connections. The number of the transport connections that are used to transfer data is selected based on the size of the data to be transferred and may change after transfer of data has commenced based on the amount of data left and the attributes of the transport connections. In another aspect, data to be transmitted over the transport connections is organized into frames such that each frame includes data from only one data stream. The frames are sized to be less than or equal to a control window of the transport connection over which they are transmitted. Each frame may be assigned to a transport connection in a round robin fashion or based on the size of the frame and the sizes of the control windows of the transport connections.

Abstract: An apparatus and method for gesture detection and recognition. The apparatus includes a processing element, a radar sensor, a depth sensor, and an optical sensor. The radar sensor, the depth sensor, and the optical sensor are coupled to the processing element, and the radar sensor, the depth sensor, and the optical sensor are configured for short range gesture detection and recognition. The processing element is further configured to detect and recognize a hand gesture based on data acquired with the radar sensor, the depth sensor, and the optical sensor.

Abstract: A client and content provider are connected by a plurality of simultaneous transport connections. The number of the transport connections that are used to transfer data is selected based on the size of the data to be transferred and may change after transfer of data has commenced based on the amount of data left and the attributes of the transport connections. In another aspect, data to be transmitted over the transport connections is organized into frames such that each frame includes data from only one data stream. The frames are sized to be less than or equal to a control window of the transport connection over which they are transmitted. Each frame may be assigned to a transport connection in a round robin fashion or based on the size of the frame and the sizes of the control windows of the transport connections.

Abstract: An apparatus and method for radar based gesture detection. The apparatus includes a processing element and a transmitter configured to transmit radar signals. The transmitter is coupled to the processing element. The apparatus further includes a plurality of receivers configured to receive radar signal reflections, where the plurality of receivers is coupled to the processing element. The transmitter and plurality of receivers are configured for short range radar and the processing element is configured to detect a hand gesture based on the radar signal reflections received by the plurality of receivers.

Abstract: A client and content provider are connected by a plurality of simultaneous transport connections. The number of the transport connections that are used to transfer data is selected based on the size of the data to be transferred and may change after transfer of data has commenced based on the amount of data left and the attributes of the transport connections. In another aspect, data to be transmitted over the transport connections is organized into frames such that each frame includes data from only one data stream. The frames are sized to be less than or equal to a control window of the transport connection over which they are transmitted. Each frame may be assigned to a transport connection in a round robin fashion or based on the size of the frame and the sizes of the control windows of the transport connections.

Abstract: A client and content provider are connected by a plurality of simultaneous transport connections. The number of the transport connections that are used to transfer data is selected based on the size of the data to be transferred and may change after transfer of data has commenced based on the amount of data left and the attributes of the transport connections. In another aspect, data to be transmitted over the transport connections is organized into frames such that each frame includes data from only one data stream. The frames are sized to be less than or equal to a control window of the transport connection over which they are transmitted. Each frame may be assigned to a transport connection in a round robin fashion or based on the size of the frame and the sizes of the control windows of the transport connections.