- 专利标题: ADVERSARIAL DETECTION USING DISCRIMINATOR MODEL OF GENERATIVE ADVERSARIAL NETWORK ARCHITECTURE
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申请号: US18135046申请日: 2023-04-14
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公开(公告)号: US20240005651A1公开(公告)日: 2024-01-04
- 发明人: Miriam Hanna Manevitz , Aviv Ben Arie
- 申请人: Intuit Inc.
- 申请人地址: US CA Mountain View
- 专利权人: Intuit Inc.
- 当前专利权人: Intuit Inc.
- 当前专利权人地址: US CA Mountain View
- 主分类号: G06V10/82
- IPC分类号: G06V10/82 ; G06N3/045 ; G06V10/774
摘要:
A method includes training, using first real data objects, a generative adversarial network having a generator model and a discriminator model to create a trained generator model that generates realistic data, and training, using adversarial data objects and second real data objects, the discriminator model to output an authenticity binary class for the adversarial data objects and the second real data objects. The method further includes deploying the discriminator model to a production system. In the production system, the discriminator model outputs the authenticity binary class to a system classifier model.
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