Invention Grant
- Patent Title: Using empirical evidence to generate synthetic training data for plant detection
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Application No.: US17463360Application Date: 2021-08-31
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Publication No.: US11544920B2Publication Date: 2023-01-03
- Inventor: Lianghao Li , Kangkang Wang , Zhiqiang Yuan
- Applicant: X Development LLC
- Applicant Address: US CA Mountain View
- Assignee: X Development LLC
- Current Assignee: X Development LLC
- Current Assignee Address: US CA Mountain View
- Agency: Middleton Reutlinger
- Main IPC: G06K9/62
- IPC: G06K9/62 ; G06V20/10 ; G06N3/08

Abstract:
Implementations are described herein for automatically generating synthetic training images that are usable as training data for training machine learning models to detect, segment, and/or classify various types of plants in digital images. In various implementations, a digital image may be obtained that captures an area. The digital image may depict the area under a lighting condition that existed in the area when a camera captured the digital image. Based at least in part on an agricultural history of the area, a plurality of three-dimensional synthetic plants may be generated. The synthetic training image may then be generated to depict the plurality of three-dimensional synthetic plants in the area. In some implementations, the generating may include graphically incorporating the plurality of three-dimensional synthetic plants with the digital image based on the lighting condition.
Public/Granted literature
- US20210397836A1 USING EMPIRICAL EVIDENCE TO GENERATE SYNTHETIC TRAINING DATA FOR PLANT DETECTION Public/Granted day:2021-12-23
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