Invention Grant
- Patent Title: Determining contextual confidence of images using associative deep learning
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Application No.: US16129095Application Date: 2018-09-12
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Publication No.: US10970331B2Publication Date: 2021-04-06
- Inventor: Todd R. Whitman , Aaron K. Baughman , John P. Perrino , Diwesh Pandey
- Applicant: International Business Machines Corporation
- Applicant Address: US NY Armonk
- Assignee: International Business Machines Corporation
- Current Assignee: International Business Machines Corporation
- Current Assignee Address: US NY Armonk
- Agency: Garg Law Firm, PLLC
- Agent Rakesh Garg; James Nock
- Main IPC: G06K9/62
- IPC: G06K9/62 ; G06F16/58 ; G06F17/18 ; G06K9/32 ; G06F16/35 ; G06F40/30

Abstract:
Determining contextual confidence of images for associative deep learning includes receiving an image including a representation of a subject. Text data related to the image is received. One or more physical properties of the image are determined. Context information of the image is determined using natural language processing. The image is classified based upon the contextual information and the one or more physical properties using a classification model to determine a classification. An emotional state of the image is determined based upon the physical properties. A confidence of the classification and emotional state is determined.
Public/Granted literature
- US20200082002A1 DETERMINING CONTEXTUAL CONFIDENCE OF IMAGES USING ASSOCIATIVE DEEP LEARNING Public/Granted day:2020-03-12
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