Invention Grant
- Patent Title: Entropy based synthetic data generation for augmenting classification system training data
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Application No.: US16659147Application Date: 2019-10-21
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Publication No.: US11423264B2Publication Date: 2022-08-23
- Inventor: Pinkesh Badjatiya , Nikaash Puri , Ayush Chopra , Anubha Kabra
- Applicant: Adobe Inc.
- Applicant Address: US CA San Jose
- Assignee: Adobe Inc.
- Current Assignee: Adobe Inc.
- Current Assignee Address: US CA San Jose
- Agency: FIG. 1 Patents
- Main IPC: G06K9/62
- IPC: G06K9/62 ; G06N20/10

Abstract:
A data classification system is trained to classify input data into multiple classes. The system is initially trained by adjusting weights within the system based on a set of training data that includes multiple tuples, each being a training instance and corresponding training label. Two training instances, one from a minority class and one from a majority class, are selected from the set of training data based on entropies for the training instances. A synthetic training instance is generated by combining the two selected training instances and a corresponding training label is generated. A tuple including the synthetic training instance and the synthetic training label is added to the set of training data, resulting in an augmented training data set. One or more such synthetic training instances can be added to the augmented training data set and the system is then re-trained on the augmented training data set.
Public/Granted literature
- US20210117718A1 Entropy Based Synthetic Data Generation For Augmenting Classification System Training Data Public/Granted day:2021-04-22
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