Invention Grant
- Patent Title: Data augmentation in training deep neural network (DNN) based on genetic model
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Application No.: US16409443Application Date: 2019-05-10
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Publication No.: US11461657B2Publication Date: 2022-10-04
- Inventor: Ripon Saha , Xiang Gao , Mukul Prasad
- Applicant: FUJITSU LIMITED
- Applicant Address: JP Kawasaki
- Assignee: FUJITSU LIMITED
- Current Assignee: FUJITSU LIMITED
- Current Assignee Address: JP Kawasaki
- Agency: Fujitsu Patent Center
- Main IPC: G06N3/02
- IPC: G06N3/02 ; G06N3/08 ; G06N3/04 ; G06F7/58 ; G10L15/16 ; G06K9/62 ; G06F17/18

Abstract:
According to an aspect of an embodiment, operations may include selecting, from a training dataset, a first data point as a seed data point. The operations may further include generating a population of data points by application of a genetic model on the seed data point. The population of data points may include the seed data point and a plurality of transformed data points of the seed data point. The operations may further include determining a best-fit data point in the generated population of data points based on application of a fitness function on the generated population of data points. The operations may further include executing a training operation on the DNN based on the determined best-fit data point. The operations may further include obtaining a trained DNN for the first data point based on the training operation on the DNN based on the determined best-fit data point.
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