Invention Grant
- Patent Title: Bi-level specificity content annotation using an artificial neural network
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Application No.: US16509422Application Date: 2019-07-11
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Publication No.: US10891985B1Publication Date: 2021-01-12
- Inventor: Miquel Angel Farre Guiu , Monica Alfaro Vendrell , Albert Aparicio Isarn , Daniel Fojo , Marc Junyent Martin , Anthony M. Accardo , Avner Swerdlow
- Applicant: Disney Enterprises, Inc.
- Applicant Address: US CA Burbank
- Assignee: Disney Enterprises, Inc.
- Current Assignee: Disney Enterprises, Inc.
- Current Assignee Address: US CA Burbank
- Agency: Farjami & Farjami LLP
- Main IPC: H04N9/80
- IPC: H04N9/80 ; G11B27/00 ; G11B27/34 ; G06K9/00 ; G06N3/08 ; G06N3/04 ; G11B27/19 ; H04N5/93 ; H04N5/78 ; H04N5/92

Abstract:
A content annotation system includes a computing platform having a hardware processor and a memory storing a tagging software code including an artificial neural network (ANN). The hardware processor executes the tagging software code to receive content having a content interval including an image of a generic content feature, encode the image into a latent vector representation of the image using an encoder of the ANN, and use a first decoder of the ANN to generate a first tag describing the generic content feature based on the latent vector representation. When a specific content feature learned by the ANN corresponds to the generic content to feature described by the first tag, the tagging software code uses a second decoder of the ANN to generate a second tag uniquely identifying the specific content feature based on the latent vector representation, and tags the content interval with the first and second tags.
Public/Granted literature
- US20210012813A1 Bi-Level Specificity Content Annotation Using an Artificial Neural Network Public/Granted day:2021-01-14
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