The following operators can be used to better focus your queries.
( ) , AND, OR, NOT, W/#
? single char wildcard, not at start
* multi char wildcard, not at start
(Cat? OR feline) AND NOT dog?
Cat? W/5 behavior
(Cat? OR feline) AND traits
Cat AND charact*
This guide provides a more detailed description of the syntax that is supported along with examples.
This search box also supports the look-up of an IP.com Digital Signature (also referred to as Fingerprint); enter the 72-, 48-, or 32-character code to retrieve details of the associated file or submission.
Concept Search - What can I type?
For a concept search, you can enter phrases, sentences, or full paragraphs in English. For example, copy and paste the abstract of a patent application or paragraphs from an article.
Concept search eliminates the need for complex Boolean syntax to inform retrieval. Our Semantic Gist engine uses advanced cognitive semantic analysis to extract the meaning of data. This reduces the chances of missing valuable information, that may result from traditional keyword searching.
A program is disclosed that provides multiple graphical views to do an in depth comparison between automatic multi-modal recognition results.
English (United States)
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System and Method for Analyzing Multimedia Modality Results
Manual labeling of events, scenes, and objects in multimedia content is an arduous task. Automatic recognition and indexing of multimedia using semantic concept models is becoming a reality. The eventual labeling of multimedia content consists of applying multiple semantic concept models to evaluate the confidence that a semantic concept is present in the content. The various model results are then combined via a weighting function, to give a confidence that the concept is present in the content. Prior to this solution, model results were displayed as confidence ordered thumbnails which could be played back to observe the actual content. In addition, as a separate process, precision recall curves were generated in a graphing program.
The program inputs the results from several models for a variety of semantic concepts. The user may then select a particular semantic concept to analyze. The program will display up to 5 models for a given concept. If more than 5 models exist for the concept, the user may select which 5 models to display. In addition, a list of manually annotated results and a truth table for the selected concept are also displayed. The figure below is a sample of the analysis screen.
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The current concept, in this case "face" is displayed in the upper left corner. The truth table appears immediately below it. The middle three list boxes display the results for the models detecting the concept "face". The title of each list box is the...