Invention Grant
- Patent Title: Method of generating data by using artificial neural network model having encoder-decoder structure
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Application No.: US17880415Application Date: 2022-08-03
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Publication No.: US11887002B2Publication Date: 2024-01-30
- Inventor: Seongmin Park , Jihwa Lee
- Applicant: ActionPower Corp.
- Applicant Address: KR Seoul
- Assignee: ActionPower Corp.
- Current Assignee: ActionPower Corp.
- Current Assignee Address: KR Seoul
- Agency: Fish IP Law, LLP
- Priority: KR 20220073324 2022.06.16
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06N3/082 ; G06N3/04

Abstract:
Disclosed is a method of generating data based on input data by using a pre-trained artificial neural network model having an encoder-decoder structure. In particular, according to the present disclosure, a computing device generates new data based on a probability distribution of input data by using a pre-trained artificial neural network model having an encoder-decoder structure, and the pre-trained artificial neural network model having the encoder-decoder structure corresponds to a pre-trained model in which a latent vector layer is included between an encoder layer and a decoder layer of the artificial neural network model.
Public/Granted literature
- US20230409913A1 METHOD OF GENERATING DATA BY USING ARTIFICIAL NEURAL NETWORK MODEL HAVING ENCODER-DECODER STRUCTURE Public/Granted day:2023-12-21
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