Invention Grant
- Patent Title: Data augmentation for domain generalization
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Application No.: US17716590Application Date: 2022-04-08
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Publication No.: US12277696B2Publication Date: 2025-04-15
- Inventor: Laura Beggel , Filipe J. Cabrita Condessa , Robin Hutmacher , Jeremy Kolter , Nhung Thi Phuong Ngo , Fatemeh Sheikholeslami , Devin T. Willmott
- Applicant: Robert Bosch GmbH
- Applicant Address: DE Stuttgart
- Assignee: Robert Bosch GmbH
- Current Assignee: Robert Bosch GmbH
- Current Assignee Address: DE Stuttgart
- Agency: Dickinson Wright PLLC
- Main IPC: G06T7/00
- IPC: G06T7/00 ; G06N20/00 ; G06T7/11 ; G06T7/194

Abstract:
Methods and systems are disclosed for generating training data for a machine learning model for better performance of the model. A source image is selected from an image database, along with a target image. An image segmenter is utilized with the source image to generate a source image segmentation mask having a foreground region and a background region. The same is performed with the target image to generate a target image segmentation mask having a foreground region and a background region. Foregrounds and backgrounds of the source image and target image are determined based on the masks. The target image foreground is removed from the target image, and the source image foreground is inserted into the target image to create an augmented image having the source image foreground and the target image background. The training data for the machine learning model is updated to include this augmented image.
Public/Granted literature
- US20230326005A1 DATA AUGMENTATION FOR DOMAIN GENERALIZATION Public/Granted day:2023-10-12
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