公开(公告)号：US20200250465A1

公开(公告)日：2020-08-06

申请号：US16853111

申请日：2020-04-20

Applicant: Adobe Inc.

Inventor： ZHE LIN ,  XIAOHUI SHEN ,  JONATHAN BRANDT ,  JIANMING ZHANG ,  CHEN FANG

IPC: G06K9/62 ,  G06F16/51 ,  G06F16/28 ,  G06F16/2457 ,  G06K9/46 ,  G06F16/583 ,  G06N3/04 ,  G06N3/08

Abstract: Embodiments of the present invention provide an automated image tagging system that can predict a set of tags, along with relevance scores, that can be used for keyword-based image retrieval, image tag proposal, and image tag auto-completion based on user input. Initially, during training, a clustering technique is utilized to reduce cluster imbalance in the data that is input into a convolutional neural network (CNN) for training feature data. In embodiments, the clustering technique can also be utilized to compute data point similarity that can be utilized for tag propagation (to tag untagged images). During testing, a diversity based voting framework is utilized to overcome user tagging biases. In some embodiments, bigram re-weighting can down-weight a keyword that is likely to be part of a bigram based on a predicted tag set.