Abstract: Image data of a first image in a sequence of images is processed using an artificial neural network (ANN) to generate output image data indicative of an alignment of the first image with a second image in the sequence. The ANN is trained using outputs of an alignment pipeline configured to perform alignment of images. The alignment pipeline is configured to determine flow vectors representing optical flow between images, and perform an image transformation using the flow vectors to align the images. The ANN is trained to emulate a result derivable using the alignment pipeline.

Abstract: Image data representing one or more images at a first resolution is received at a first artificial neural network (ANN). The image data is processed using the first ANN to generate upscaled image data representing the one or more images at a second, higher resolution. The first ANN is trained to perform image upscaling and is trained using first training image data representing one or more training images at the first resolution, the first training image data being at a first level of quality. The first ANN is also trained using features of a second ANN, wherein the second ANN is trained to perform image upscaling and is trained using second training image data representing one or more training images at the first resolution, the second training image data being at a second level of quality, higher than the first level of quality.

Abstract: Systems, devices, methods, and non-transitory computer-readable instructions for detecting deception of a subject from a media stream that capture a media stream of the subject including, the media stream including a sequence of frames, process each frame of the media stream to track a plurality of biometrics, and determine whether the subject in the media stream is deceptive based upon changes to respective biometrics.

Abstract: A system receives locations of a plurality of electricity-generating units in an area, and it divides the area into a plurality of sectors. The system traverses through the sectors and forms a set of sectors. The set of sectors includes a set of electricity-generating units. The set of electricity-generating units does not exceed an aggregate voltage threshold. The system forms a circuit with the set of electricity-generating units by determining a shortest path to connect the set of electricity-generating units. The system adjusts this shortest path to incorporate environmental and physical constraints.

Abstract: A method for distributed training in a parameter dataset; the method for at least one coordinating node; a network of at least one distributed node; receiving a parameter dataset from a first distributed node; decrypting the received dataset; training the parameter dataset based on a training data record to obtain a trained parameter dataset; and forwarding the trained parameter dataset to a second distributed node.

Abstract: A system receives locations of a plurality of electricity-generating units in an area, and it divides the area into a plurality of sectors. The system traverses through the sectors and forms a set of sectors. The set of sectors includes a set of electricity-generating units. The set of electricity-generating units does not exceed an aggregate voltage threshold. The system forms a circuit with the set of electricity-generating units by determining a shortest path to connect the set of electricity-generating units. The system adjusts this shortest path to incorporate environmental and physical constraints.

Abstract: A method for distributed training in a parameter dataset; the method for at least one coordinating node; a network of at least one distributed node; receiving a parameter dataset from a first distributed node; decrypting the received dataset; training the parameter dataset based on a training data record to obtain a trained parameter dataset; and forwarding the trained parameter dataset to a second distributed node.

Abstract: Disclosed are a depth refinement system and a method for a sparse depth image in a multi-aperture camera. The method includes providing a sparse depth map generated based on an image obtained through each of a plurality of apertures included in the multi-aperture camera, wherein the sparse depth map includes depths of pixels included in the image, and performing a depth noise reduction (DNR) based on the sparse depth map.

Abstract: Systems for treating premature ejaculation include an electrical pulse generator and electrical leads in communication with sympathetic nerves serving ejaculatory structures. The system inhibits sympathetic nerve input to the ejaculatory structure with electrical impulses from the electrical pulse generator. The duration of inhibition may be predetermined or selectable. The system may be operated with user-actuated controls, a sensor and a timer, or combinations of these elements.