Abstract: At least some aspects of the present disclosure feature systems and methods for obfuscating data. The method includes the steps of: receiving an input data stream comprising a sequence of n-grams; mapping at least some of the sequence of n-grams to corresponding dictionary terms using an dictionary; disposing the corresponding tokens to an output data stream.

Abstract: Methods for estimating and predicting tooth wear based upon a single 3D digital model of teeth. The 3D digital model is segmented to identify individual teeth within the model. A digital model of a tooth is selected from the segmented model, and its original shape is predicted. The digital model is compared with the predicted original shape to estimate wear areas. A mapping function based upon values relating to tooth wear can also be applied to the selected digital model to predict wear of the tooth.

Abstract: At least some aspects of the present disclosure feature systems and methods for note recognition. The note recognition system includes a sensor, a note recognition module, and a note extraction module. The sensor is configured to capture a visual representation of a scene having one or more notes. The note recognition module is coupled to the sensor. The note recognition module is configured to receive the captured visual representation and determine a general boundary of a note from the captured visual representation. The note extraction module is configured to extract content of the note from the captured visual representation based on the determined general boundary of the note.

Abstract: At least some embodiments of the present disclosure feature systems and methods for assessing the impact of visual features within a region of a scene. With the input of a visual representation of a scene and at least one selected region within the scene, the system applies a visual attention model to the visual representation to determine visual conspicuity of the at least one selected region. The system computes feature-related data associated with a plurality of features of the at least one selected region. Based on the visual conspicuity and the feature-related data, the system assesses an impact that at least one of the features within the at least one selected region have on the visual conspicuity.

Abstract: At least some aspects of the present disclosure feature systems and methods for note recognition. The note recognition system includes a sensor, a note recognition module, and a note extraction module. The sensor is configured to capture a visual representation of a scene having one or more notes. The note recognition module is coupled to the sensor. The note recognition module is configured to receive the captured visual representation and determine a general boundary of a note from the captured visual representation. The note extraction module is configured to extract content of the note from the captured visual representation based on the determined general boundary of the note.

Abstract: Systems and methods for optimizing properties of objects within a scene or achieve a visual goal.

Abstract: At least some aspects of the present disclosure feature systems and methods for note recognition. The note recognition system includes a sensor, a note recognition module, and a note extraction module. The sensor is configured to capture a visual representation of a scene having one or more notes. The note recognition module is coupled to the sensor. The note recognition module is configured to receive the captured visual representation and determine a general boundary of a note from the captured visual representation. The note extraction module is configured to extract content of the note from the captured visual representation based on the determined general boundary of the note.

Abstract: A mobile device comprises a sensor to produce image data containing a visual representation of a plurality of physical notes, each of the physical notes comprising separate physical objects, a processor, and at least one module. The module can process the image data to determine boundaries for each of the plurality of physical notes and to determine, based on the boundaries, one or more characteristics for each of the physical notes. The module can also create a digital note representative of each of the plurality of physical notes, apply a set of rules to identify any of the rules that specify criteria satisfied by one or more characteristics of the physical notes, and for each of the identified rules, perform one or more actions specified by the rule to each of the digital notes for which the characteristics of the physical notes satisfies the criteria specified by the rule.

Abstract: At least some aspects of the present disclosure feature systems and methods for note recognition. The note recognition system includes a sensor, a note recognition module, and a note extraction module. The sensor is configured to capture a visual representation of a scene having one or more notes. The note recognition module is coupled to the sensor. The note recognition module is configured to receive the captured visual representation and determine a general boundary of a note from the captured visual representation. The note extraction module is configured to extract content of the note from the captured visual representation based on the determined general boundary of the note.

Abstract: At least some aspects of the present disclosure feature systems and methods for managing notes. The note management system includes a note source, a note recognition module, a note extraction module, and a note labeling module. The note source is a visual representation of a scene having a note. The note recognition module is configured to receive the visual representation and determine a general boundary of the note from the visual representation. The note extraction module is configured to extract content of the note from the visual representation based on the determined general boundary. The note labeling module is configured to label the note with a category.

Abstract: Systems and methods for evaluating the robustness of objects within a scene or a scene itself.

Abstract: Systems and methods for using visual attention modeling techniques to evaluate a scene from multiple perspectives.

Abstract: Systems and methods for optimizing properties of objects within a scene or achieve a visual goal.

Abstract: The present invention is directed to systems, articles, and computer-implemented methods for assessing effectiveness of communication content and optimizing content distribution to enhance business objectives. Embodiments of the present invention are directed to computer-implemented methods for a computer-implemented method, comprising conducting an experiment using experimental content to determine effectiveness of communication content and executing, while conducting the experiment, a machine learning routine (MLR) using MLR content to enhance an effectiveness metric.

Abstract: Systems and methods for evaluating the robustness of objects within a scene or a scene itself.

Abstract: Systems and methods for optimizing properties of objects within a scene or achieve a visual goal.

Abstract: Systems and methods for improving visual attention models use effectiveness assessment from an environment as feedback to improve visual attention models. The effectiveness assessment uses data indicative of a particular behavior, which is related to visual attention allocation, received from the environment to assess relative effectiveness of the environment on influencing the particular behavior.

Abstract: The present invention is directed to systems, articles, and computer-implemented methods for assessing effectiveness of communication content and optimizing content distribution to enhance business objectives. Embodiments of the present invention are directed to computer-implemented methods for a computer-implemented method, comprising conducting an experiment using experimental content to determine effectiveness of communication content and executing, while conducting the experiment, a machine learning routine (MLR) using MLR content to enhance an effectiveness metric.

Abstract: Systems and methods for evaluating the robustness of objects within a scene or a scene itself.

Abstract: The present invention is directed to systems, articles, and computer-implemented methods for assessing effectiveness of communication content and optimizing content distribution to enhance business objectives. Embodiments of the present invention are directed to computer-implemented methods for a computer-implemented method, comprising conducting an experiment using experimental content to determine effectiveness of communication content and executing, while conducting the experiment, a machine learning routine (MLR) using MLR content to enhance an effectiveness metric.