Invention Grant
- Patent Title: Domain adaptation of deep neural networks
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Application No.: US16727429Application Date: 2019-12-26
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Publication No.: US11580405B2Publication Date: 2023-02-14
- Inventor: Erick David Santillán Perez , David Kernert
- Applicant: SAP SE
- Applicant Address: DE Walldorf
- Assignee: SAP SE
- Current Assignee: SAP SE
- Current Assignee Address: DE Walldorf
- Agency: Sterne, Kessler, Goldstein & Fox P.L.L.C.
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06N3/084 ; G06N3/04 ; G06K9/62

Abstract:
Disclosed herein are system, method, and computer program product embodiments for adapting machine learning models for use in additional applications. For example, feature extraction models are readily available for use in applications such as image detection. These feature extraction models can be used to label inputs (such as images) in conjunction with other deep neural network models. However, in adapting the feature extraction models to these uses, it becomes problematic to improve the quality of their results on target data sets, as these feature extraction models are large and resistant to retraining. Approaches disclosed herein include a transfer layer for providing fast retraining of machine learning models.
Public/Granted literature
- US20210201152A1 DOMAIN ADAPTATION OF DEEP NEURAL NETWORKS Public/Granted day:2021-07-01
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