发明公开
- 专利标题: GENERATING SYNTHETIC MODELS OR VIRTUAL OBJECTS FOR TRAINING A DEEP LEARNING NETWORK
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申请号: EP20152426.1申请日: 2020-01-17
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公开(公告)号: EP3683727A1公开(公告)日: 2020-07-22
- 发明人: FARIVAR, Reza , TAYLOR, Kenneth , WALTERS, Austin , FORD, Jospeh , ADHIKARI, Rittika
- 申请人: Capital One Services, LLC
- 申请人地址: 1680 Capital One Drive McLean, Virginia 22102 US
- 专利权人: Capital One Services, LLC
- 当前专利权人: Capital One Services, LLC
- 当前专利权人地址: 1680 Capital One Drive McLean, Virginia 22102 US
- 代理机构: Müller-Boré & Partner Patentanwälte PartG mbB
- 优先权: US201916250719 20190117
- 主分类号: G06K9/62
- IPC分类号: G06K9/62 ; G06N3/08 ; G06K9/00
摘要:
In some implementations, a training platform may receive data for generating synthetic models of a body part, such as a hand. The data may include information relating to a plurality of potential poses of the hand. The training platform may generate a set of synthetic models of the hand based on the information, where each synthetic model, in the set of synthetic models, representing a respective pose of the plurality of potential poses. The training platform may derive an additional set of synthetic models based on the set of synthetic models by performing one or more processing operations with respect to at least one synthetic model in the set of synthetic models, and causing the set of synthetic models and the additional set of synthetic models to be provided to a deep learning network to train the deep learning network to perform image segmentation, object recognition, or motion recognition.
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