Abstract: Systems and techniques that synthesize an image with similar texture to a selected style image. A generator network is trained to synthesize texture images depending on a selection unit input. The training configures the generator network to synthesize texture images that are similar to individual style images of multiple style images based on which is selected by the selection unit input. The generator network can be configured to minimize a covariance matrix-based style loss and/or a diversity loss in synthesizing the texture images. After training the generator network, the generator network is used to synthesize texture images for selected style images. For example, this can involve receiving user input selecting a selected style image, determining the selection unit input based on the selected style image, and synthesizing texture images using the generator network with the selection unit input and noise input.

Abstract: Embedding space for images with multiple text labels is described. In the embedding space both text labels and image regions are embedded. The text labels embedded describe semantic concepts that can be exhibited in image content. The embedding space is trained to semantically relate the embedded text labels so that labels like “sun” and “sunset” are more closely related than “sun” and “bird”. Training the embedding space also includes mapping representative images, having image content which exemplifies the semantic concepts, to respective text labels. Unlike conventional techniques that embed an entire training image into the embedding space for each text label associated with the training image, the techniques described herein process a training image to generate regions that correspond to the multiple text labels. The regions of the training image are then embedded into the training space in a manner that maps the regions to the corresponding text labels.

Abstract: An engine assembly includes an engine with an engine block having at least one cylinder. A crankshaft is moveable to define a plurality of crank angles from a bore axis defined by the cylinder to a crank axis defined by the crankshaft. The plurality of angles includes a crank angle (CA50) corresponding to 50% of the fuel received by the cylinder being combusted. A controller is operatively connected to the engine and has a processor and a tangible, non-transitory memory on which is recorded instructions for executing a method for controlling the combustion phasing in the engine during a transient state. The controller is programmed to generate a learned table by storing at least one combustion phasing parameter in the tangible, non-transitory memory. Combustion phasing during a transient state is controlled based at least partially on the learned table.

Abstract: Methods and systems are provided for ranking images against queries. A visual modality ranking of visual features of a digital image against a query is generated. A language modality ranking of text features of text associated with the digital image against the query is also generated. A multi-modal neural network determines importance weightings of the language modality ranking and the visual modality ranking against the query. The visual modality ranking and the language modality ranking are combined into a multi-modal ranking of the digital image against the query based on the importance weightings. The digital image is provided as a search result of the query based on the multi-modal ranking.

Abstract: This disclosure involves personalizing user experiences with electronic content based on application usage data. For example, a user representation model that facilitates content recommendations is iteratively trained with action histories from a content manipulation application. Each iteration involves selecting, from an action history for a particular user, an action sequence including a target action. An initial output is computed in each iteration by applying a probability function to the selected action sequence and a user representation vector for the particular user. The user representation vector is adjusted to maximize an output that is generated by applying the probability function to the action sequence and the user representation vector. This iterative training process generates a user representation model, which includes a set of adjusted user representation vectors, that facilitates content recommendations corresponding to users' usage pattern in the content manipulation application.

Abstract: Methods and systems are provided for transforming sketches into stylized electronic paintings. A neural network system is trained where the training includes training a first neural network that converts input sketches into output images and training a second neural network that converts images into output paintings. Similarity for the first neural network is evaluated between the output image and a reference image and similarity for the second neural network is evaluated between the output painting, the output image, and a reference painting. The neural network system is modified based on the evaluated similarity. The trained neural network is used to generate an output painting from an input sketch where the output painting maintains features from the input sketch utilizing an extrapolated intermediate image and reflects a designated style from the reference painting.

Abstract: A digital medium environment includes an asset processing application that performs editing of assets. A projection function is trained using pairs of actions pertaining to software edits, and assets resulting from the actions to learn a joint embedding between the actions and the assets. The projection function is used in the asset processing application to recommend software actions to create an asset, and also to recommend assets to demonstrate the effects of software actions. Recommendations are based on ranking distance measures that measure distances between actions representations and asset representations in a vector space.

Abstract: A tunable antenna module for a mobile device includes an antenna, a frequency-division circuit and one or more impedance-tuning circuits. The frequency-division circuit is coupled to a radiator of the antenna for forming one or more signal paths for one or more of component frequencies of a radio-frequency signal of the antenna. One or more the impedance-tuning circuits are coupled to the frequency-division circuit for tuning an impedance of the antenna at one or more of the component frequencies of the radio-frequency signal.

Abstract: A vehicle includes a combustion engine having at least one cylinder to burn a fuel and a fuel injector to selectively supply fuel to the cylinder. The vehicle also includes a controller programmed to issue a series of fuel pulse commands to actuate the fuel injector to supply a corresponding series of fuel pulses that sum to an aggregate target fuel mass. The controller also monitors a closed-loop feedback signal indicative of a change in an opening delay between an individual one of the series of fuel pulse commands and a responsive fuel pulse. The controller is further programmed to adjust a subsequent one of the series of fuel pulse commands to incorporate the change in opening delay.

Abstract: Embodiments of the present invention relate to learning image representation by distilling from multi-task networks. In implementation, more than one single-task network is trained with heterogeneous labels. In some embodiments, each of the single-task networks is transformed into a Siamese structure with three branches of sub-networks so that a common triplet ranking loss can be applied to each branch. A distilling network is trained that approximates the single-task networks on a common ranking task. In some embodiments, the distilling network is a Siamese network whose ranking function is optimized to approximate an ensemble ranking of each of the single-task networks. The distilling network can be utilized to predict tags to associate with a test image or identify similar images to the test image.

Abstract: The present disclosure includes methods and systems for searching for digital visual media based on semantic and spatial information. In particular, one or more embodiments of the disclosed systems and methods identify digital visual media displaying targeted visual content in a targeted region based on a query term and a query area provide via a digital canvas. Specifically, the disclosed systems and methods can receive user input of a query term and a query area and provide the query term and query area to a query neural network to generate a query feature set. Moreover, the disclosed systems and methods can compare the query feature set to digital visual media feature sets. Further, based on the comparison, the disclosed systems and methods can identify digital visual media portraying targeted visual content corresponding to the query term within a targeted region corresponding to the query area.

Abstract: Disclosed are engine torque and emission control (ETEC) systems, methods for using such systems, and motor vehicles with engines employing ETEC schemes. An ETEC system is disclosed for operating an internal combustion engine (ICE) assembly. The system includes an engine sensor for monitoring engine torque, an exhaust sensor for monitoring nitrogen oxide (NOx) output of the ICE assembly, and an engine control unit (ECU) communicatively connected to the engine sensor, exhaust sensor, and ICE assembly.

Abstract: A vehicle propulsion system includes a combustion engine configured to output a propulsion torque to satisfy a propulsion demand, and a traction electric machine to generate a supplemental torque to selectively supplement the propulsion torque. The propulsion system also includes a controller programmed to forecast an acceleration demand based on at least one estimation model. The controller is also programmed to issue a command indicative of a required axle torque corresponding to the acceleration demand. The controller is further programmed to engage at least one fuel conservation action in response to the required axle torque being within a first predetermined torque threshold range.

Abstract: A system according to the principles of the present disclosure includes a pedal position prediction module and an engine actuator control module. The pedal position prediction module predicts a pedal position at a future time based on driver behavior and vehicle driving conditions. The pedal position includes at least one of an accelerator pedal position and a brake pedal position. The engine actuator control module controls an actuator of an engine based on the predicted pedal position.

Abstract: An interface module for a communication device includes a first switch, for forming a first connection between a first feeding point of an antenna of the communication device and one of a first matching component and a first grounding component; a second switch, for forming a second connection between a second feeding point of the antenna and one of a second matching component and a second grounding component; and a third switch, for forming a third connection between a transceiver and one of the first matching component and the first grounding component.

Abstract: A tunable antenna module for a mobile device includes an antenna, a frequency-division circuit and one or more impedance-tuning circuits. The frequency-division circuit is coupled to a radiator of the antenna for forming one or more signal paths for one or more of component frequencies of a radio-frequency signal of the antenna. One or more the impedance-tuning circuits are coupled to the frequency-division circuit for tuning an impedance of the antenna at one or more of the component frequencies of the radio-frequency signal.

Abstract: An internal combustion engine is described. Controlling the internal combustion engine includes gathering engine operating data during steady-state engine operation, including gathering a first dataset associated with a cylinder air charge during steady-state operation of the engine in the PVO state and gathering a second dataset associated with a cylinder air charge during steady-state operation of the engine in the NVO state. An optimization routine is executed to determine a first subset of parameters associated with a first relationship for a cylinder air charge model based upon the second dataset. The optimization routine is also executed to determine a second subset of parameters associated with a second relationship for the cylinder air charge model based upon the first dataset. A cylinder air charge is determined in real-time during engine operation based upon the cylinder air charge model and the first and second subsets of parameters.

Abstract: A vehicle is described, and includes a drivetrain system including an internal combustion engine and a geartrain, an accessory device, and a route monitoring system. A controller includes an instruction set to monitor operation of the accessory device, and a request to operate the accessory device. When the request to operate the accessory device includes a request to activate the accessory device based upon not exceeding a limit for an operating parameter of the accessory device, the instruction set executes to determine a horizon for the vehicle based upon the projected path for the vehicle, determine a projected road load and a speed constraint based upon the horizon for the vehicle, and determine a projected axle torque command based upon the projected road load. A first routine determines a first command for operating the accessory device that minimizes fuel consumption and meets the projected axle torque command.

Abstract: A vehicle engine system includes a combustion engine configured to provide a propulsion torque to satisfy a propulsion demand in response to a driver input. The engine system also includes a controller programmed to receive data indicative of at least one upcoming driving event, and issue a command to impart a predetermined velocity profile based on the upcoming driving event. The predetermined velocity profile is arranged to optimize a performance attribute of the combustion engine and preempt the driver input.