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公开(公告)号:US20250088556A1
公开(公告)日:2025-03-13
申请号:US18956281
申请日:2024-11-22
Inventor: Pu CHEN , Qiaobo LIAO
IPC: H04L67/1097 , G06F21/62 , H04L9/40
Abstract: A model training system includes a cloud data storage platform and a cloud model training platform. The cloud data storage platform is configured to: store training data; and receive a training data calling request, and export training data corresponding to a data calling instruction to the cloud model training platform based on the training data calling request. The cloud model training platform is configured to: receive a model training creation instruction to obtain a to-be-trained model; generate the training data calling request, and send the training data calling request to the cloud data storage platform; and train the to-be-trained model by using the training data exported from the cloud data storage platform, to obtain a training result model. In the technical solutions of the present invention, a risk of leaking training data can be reduced.
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公开(公告)号:US20240119130A1
公开(公告)日:2024-04-11
申请号:US18339458
申请日:2023-06-22
Inventor: Ziwen HU , Anping LI , Xiaoyuan YU , Pu CHEN
CPC classification number: G06F21/32 , G06V40/161 , G06V40/40
Abstract: A front-end device is configured to capture a light point image of an authenticatee and send the light point image to the back-end device, where the light point image is an image captured from the authenticatee under irradiation of multi-light points, and the light point image includes a face of the authenticatee. The back-end device of the authentication system is configured to perform face anti-spoofing detection on the authenticatee based on the received light point image to obtain an authentication result.
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公开(公告)号:US20230298348A1
公开(公告)日:2023-09-21
申请号:US18322288
申请日:2023-05-23
Inventor: Ruizhi LU , Yi XIE , Xiaoyuan YU , Pu CHEN
IPC: G06V20/40 , G06V40/10 , G06V10/74 , G06V10/776 , G06V20/50
CPC classification number: G06V20/41 , G06V20/46 , G06V40/10 , G06V10/761 , G06V10/776 , G06V20/50 , G06V10/774
Abstract: This disclosure relates to a clothing standardization detection method. In an example method, a clothing standardization detection apparatus obtains a video frame sub-image and a reference sub-image. The video frame sub-image includes an image of a first wear style of a target part of the target object in the first scenario, and the reference includes an image of a standard wear style of a target part of the reference object in the first scenario. Then, the video frame sub-image and the reference sub-image are processed by using a target model, to obtain a first processing result. The target model is a trained artificial intelligence AI model, and the first processing result indicates a similarity between the first wear style of the target part of the target object and the standard wear style of the target part of the reference object.
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