Invention Publication
- Patent Title: METHOD FOR CREATING MULTIMODAL TRAINING DATASETS FOR PREDICTING USER CHARACTERISTICS USING PSEUDO-LABELING
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Application No.: US18536856Application Date: 2023-12-12
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Publication No.: US20240193969A1Publication Date: 2024-06-13
- Inventor: Jae Woong YOO , Mi Ra LEE , Hye Dong JUNG
- Applicant: Korea Electronics Technology Institute
- Applicant Address: KR Seongnam-si
- Assignee: Korea Electronics Technology Institute
- Current Assignee: Korea Electronics Technology Institute
- Current Assignee Address: KR Seongnam-si
- Priority: KR 20220173473 2022.12.13 KR 20230036768 2023.03.21
- Main IPC: G06V20/70
- IPC: G06V20/70 ; G06V10/44 ; G06V10/74

Abstract:
There is provided a method for creating multimodal training datasets for predicting characteristics of a user by using pseudo-labeling. According to an embodiment, the method may acquire a labelled dataset in which an image of a user is labelled with personality information and may extract a multimodal feature vector from the image of the acquired labelled dataset, may acquire an un-labelled dataset in which an image of a user is not labelled with personality information and may extract a multimodal feature vector from the image of the acquired un-labelled dataset, may measure a similarity between the extracted multimodal feature vector of the labelled dataset and the multimodal feature vector of the un-labelled dataset, and may label the un-labelled dataset based on the measured similarity. Accordingly, by creating multimodal training datasets for predicting a user personality by using pseudo-labeling, training datasets may be obtained rapidly, economically and effectively.
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