Invention Grant
- Patent Title: Structured knowledge modeling and extraction from images
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Application No.: US14978350Application Date: 2015-12-22
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Publication No.: US11514244B2Publication Date: 2022-11-29
- Inventor: Scott D. Cohen , Walter Wei-Tuh Chang , Brian L. Price , Mohamed Hamdy Mahmoud Abdelbaky Elhoseiny
- Applicant: Adobe Inc.
- Applicant Address: US CA San Jose
- Assignee: Adobe Inc.
- Current Assignee: Adobe Inc.
- Current Assignee Address: US CA San Jose
- Agency: FIG. 1 Patents
- Main IPC: G06N5/02
- IPC: G06N5/02 ; G06N20/00 ; G06F40/30 ; G06N3/04

Abstract:
Techniques and systems are described to model and extract knowledge from images. A digital medium environment is configured to learn and use a model to compute a descriptive summarization of an input image automatically and without user intervention. Training data is obtained to train a model using machine learning in order to generate a structured image representation that serves as the descriptive summarization of an input image. The images and associated text are processed to extract structured semantic knowledge from the text, which is then associated with the images. The structured semantic knowledge is processed along with corresponding images to train a model using machine learning such that the model describes a relationship between text features within the structured semantic knowledge. Once the model is learned, the model is usable to process input images to generate a structured image representation of the image.
Public/Granted literature
- US20170132526A1 Structured Knowledge Modeling and Extraction from Images Public/Granted day:2017-05-11
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