- Patent Title: Identifying visually similar digital images utilizing deep learning
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Application No.: US16817234Application Date: 2020-03-12
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Publication No.: US11227185B2Publication Date: 2022-01-18
- Inventor: Zhe Lin , Xiaohui Shen , Mingyang Ling , Jianming Zhang , Jason Kuen , Brett Butterfield
- Applicant: ADOBE INC.
- Applicant Address: US CA San Jose
- Assignee: ADOBE INC.
- Current Assignee: ADOBE INC.
- Current Assignee Address: US CA San Jose
- Agency: Keller Jolley Preece
- Main IPC: G06K9/62
- IPC: G06K9/62 ; G06T7/73 ; G06K9/52

Abstract:
The present disclosure relates to systems, methods, and non-transitory computer readable media for utilizing a deep neural network-based model to identify similar digital images for query digital images. For example, the disclosed systems utilize a deep neural network-based model to analyze query digital images to generate deep neural network-based representations of the query digital images. In addition, the disclosed systems can generate results of visually-similar digital images for the query digital images based on comparing the deep neural network-based representations with representations of candidate digital images. Furthermore, the disclosed systems can identify visually similar digital images based on user-defined attributes and image masks to emphasize specific attributes or portions of query digital images.
Public/Granted literature
- US20200210763A1 IDENTIFYING VISUALLY SIMILAR DIGITAL IMAGES UTILIZING DEEP LEARNING Public/Granted day:2020-07-02
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