| Patent application number | Description | Published |
|---|
| 20100086200 | SYSTEMS AND METHODS FOR MULTI-PERSPECTIVE SCENE ANALYSIS - Systems and methods for using visual attention modeling techniques to evaluate a scene from multiple perspectives. | 04-08-2010 |
| 20100174671 | SYSTEM AND METHOD FOR CONCURRENTLY CONDUCTING CAUSE-AND-EFFECT EXPERIMENTS ON CONTENT EFFECTIVENESS AND ADJUSTING CONTENT DISTRIBUTION TO OPTIMIZE BUSINESS OBJECTIVES - 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. | 07-08-2010 |
| 20130158963 | SYSTEMS AND METHODS FOR IMPROVING VISUAL ATTENTION MODELS - 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. | 06-20-2013 |
| 20130230253 | SYSTEMS AND METHODS FOR EVALUATING ROBUSTNESS OF SALIENCY PREDICTIONS OF REGIONS IN A SCENE - Systems and methods for evaluating the robustness of objects within a scene or a scene itself. | 09-05-2013 |
| 20130246162 | SYSTEM AND METHOD FOR CONCURRENTLY CONDUCTING CAUSE-AND-EFFECT EXPERIMENTS ON CONTENT EFFECTIVENESS AND ADJUSTING CONTENT DISTRIBUTION TO OPTIMIZE BUSINESS OBJECTIVES - 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. | 09-19-2013 |
| 20130259448 | SYSTEMS AND METHODS FOR OPTIMIZING A SCENE - Systems and methods for optimizing properties of objects within a scene or achieve a visual goal. | 10-03-2013 |
| 20140294236 | SYSTEMS AND METHODS FOR NOTE RECOGNITION - 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. | 10-02-2014 |
| 20140297646 | SYSTEMS AND METHODS FOR MANAGING NOTES - 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. | 10-02-2014 |
