Abstract: Aspects of a computer implemented method for lateral control of a vehicle include the following operations carried out by computer hardware components: determining a reference steering angle for the vehicle; determining at least one control variable based on a model predictive controller using the reference steering angle; and laterally controlling the vehicle based on the at least one control variable.

Abstract: A system includes a computing device that includes a memory configured to store instructions. The system also includes a processor to execute the instructions to perform operations that include receiving an image that includes textual content in at least one font. Operations also include identifying the at least one font represented in the received image using a machine learning system. The machine learning system being trained using images representing a plurality of training fonts. A portion of the training images includes text located in the foreground and being positioned over captured background imagery.

Abstract: A system includes a computing device that includes a memory configured to store instructions. The system also includes a processor to execute the instructions to perform operations that include receiving an image that includes textual content in at least one font. Operations also include identifying the at least one font represented in the received image using a machine learning system. The machine learning system being trained using images representing a plurality of training fonts. A portion of the training images includes text located in the foreground and being positioned over captured background imagery.

Abstract: A system includes a computing device that includes a memory configured to store instructions. The system also includes a processor to execute the instructions to perform operations that include attaining data representing features of a font capable of representing one or more glyphs. Operations also include determining a rating for pairing the font and at least one other font using machine learning, the features of the font, and one or more rules included in a set of rules.

Abstract: A system includes a computing device that includes a memory configured to store instructions. The system also includes a processor to execute the instructions to perform operations that include receiving data representing a plurality of items, at least two items of the plurality of items being different. Operations also include representing each of the items in an n-dimensional space, the n-dimensional space being defined by at least one of a first dimension representing an item category of the plurality of items, a second dimension representing an item attribute of the plurality of items, and the first dimension and the second dimension. Operations also include presenting at least a two-dimensional graphical representation of a portion of the plurality of items, the at least two-dimensional graphical representation reflecting at least one of the first dimension, the second dimension, and the first dimension and the second dimension.

Abstract: A system includes a computing device that includes a memory configured to store instructions. The system also includes a processor to execute the instructions to perform operations that include receiving data representing textual information input into a user device. Operations also include analyzing the data to determine the contextual meaning of the textual information, and producing one or more messages to present information at one or more other user devices using the contextual meaning of the textual information.

Abstract: A system includes a computing device that includes a memory configured to store instructions. The system also includes a processor to execute the instructions to perform operations that include receiving data representing features of a first font and data representing features of a second font. The first font and the second font are capable of representing one or more glyphs. Operations also include receiving survey-based data representing the similarity between the first and second fonts, and, training a machine learning system using the features of the first font, the features of the second font and the survey-based data that represents the similarity between the first and second fonts.

Abstract: A system includes a computing device that includes a memory configured to store instructions. The computing device also includes a processor to execute the instructions to perform operations that include receiving information that represents a font and a portion of textual content of an asset. Operations also include identifying one or more typographical features supported by a scalable font format that are capable of being applied to the portion of the textual content based upon the received information representing the font and the portion of textual content of the asset. Operations also include presenting, by the computing device, an exclusive set of selectable representations. Each of the selectable representations represents one of the one or more identified typographical features supported by the scalable font format for initiating application of the corresponding typographical feature to the textual content of the asset.

Abstract: A system includes a computing device that includes a memory configured to store instructions. The system also includes a processor to execute the instructions to perform operations that include attaining data representing features of a font capable of representing one or more glyphs. Operations also include determining a rating for pairing the font and at least one other font using machine learning, the features of the font, and one or more rules included in a set of rules.

Abstract: A system includes a computing device that includes a memory configured to store instructions. The system also includes a processor to execute the instructions to perform operations that include receiving, at an imaging device, one or more files representing a network asset that is presentable on a display of the imaging device. At least one of the files includes data for presenting textual content of the network asset. Operations also include presenting on the display of the imaging device a portion of the network asset and textual content that corresponds to the portion of the network asset. Operations also include, as the portion of the network asset and corresponding textual content is being presented, executing operations at the imaging device to determine if textual content of at least one other portion of the network asset can be presented on the display using font characters residing at the imaging device.

Abstract: A system includes a computing device that includes a memory configured to store instructions. The system also includes a processor to execute the instructions to perform operations that include receiving data representing features of a first font and data representing features of a second font. The first font and the second font are capable of representing one or more glyphs. Operations also include receiving survey-based data representing the similarity between the first and second fonts, and, training a machine learning system using the features of the first font, the features of the second font and the survey-based data that represents the similarity between the first and second fonts.

Abstract: A system includes a computing device that includes a memory configured to store instructions. The system also includes a processor to execute the instructions to perform operations that include receiving data representing features of a first font and data representing features of a second font. The first font and the second font are capable of representing one or more glyphs. Operations also include receiving survey-based data representing the similarity between the first and second fonts, and, training a machine learning system using the features of the first font, the features of the second font and the survey-based data that represents the similarity between the first and second fonts.

Abstract: A system includes a computing device that includes a memory configured to store instructions. The system also includes a processor to execute the instructions to perform operations that include receiving data representing features of a first font and data representing features of a second font. The first font and the second font are capable of representing one or more glyphs. Operations also include receiving survey-based data representing the similarity between the first and second fonts, and, training a machine learning system using the features of the first font, the features of the second font and the survey-based data that represents the similarity between the first and second fonts.

Abstract: A system includes a computing device that includes a memory configured to store instructions. The computing device also includes a processor to execute the instructions to perform operations that include receiving information that identifies an asset presenter being executed by a computing device. Based on the identity of the asset presenter, operations include determining whether the asset presenter is capable of adjusting the spacing between adjacent font characters present in content of an asset provided across one or more networks. In response to the determination, operations include sending font information to the computing device to allow the spacing of the adjacent font characters present in the content of the asset to be adjusted for presentation by the computing device.

Abstract: A system includes a computing device that includes a memory configured to store instructions. The computing device also includes a processor to execute the instructions to perform operations that include receiving information that represents a font and a portion of textual content of an asset. Operations also include identifying one or more typographical features supported by a scalable font format that are capable of being applied to the portion of the textual content based upon the received information representing the font and the portion of textual content of the asset. Operations also include presenting, by the computing device, an exclusive set of selectable representations. Each of the selectable representations represents one of the one or more identified typographical features supported by the scalable font format for initiating application of the corresponding typographical feature to the textual content of the asset.

Abstract: A system includes a first computing device that includes a memory configured to store instructions. The first computing device also includes a processor to execute the instructions to perform operations that include receiving information that indicates whether an asset presenter being executed by a computing device is capable of presenting one or more typographic features of a web asset represented in a scalable font format. Operations also include, in response to receiving the information, sending font information to the computing device to allow the one or more typographic features of the web asset represented in the scalable font format to be presented by the computing device.