Invention Grant
- Patent Title: Training a deep neural network model to generate rich object-centric embeddings of robotic vision data
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Application No.: US17279924Application Date: 2019-09-27
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Publication No.: US11887363B2Publication Date: 2024-01-30
- Inventor: Soeren Pirk , Yunfei Bai , Pierre Sermanet , Seyed Mohammad Khansari Zadeh , Harrison Lynch
- Applicant: Google LLC
- Applicant Address: US CA Mountain View
- Assignee: GOOGLE LLC
- Current Assignee: GOOGLE LLC
- Current Assignee Address: US CA Mountain View
- Agency: Gray Ice Higdon
- International Application: PCT/US2019/053554 2019.09.27
- International Announcement: WO2020/069379A 2020.04.02
- Date entered country: 2021-03-25
- Main IPC: G06V20/10
- IPC: G06V20/10 ; B25J9/16 ; B25J13/00 ; G05B13/02 ; G06N3/08 ; G10L15/22 ; G06F18/21 ; G06F18/2413 ; G06V10/764 ; G06V10/70 ; G06V10/776 ; G06V10/82

Abstract:
Training a machine learning model (e.g., a neural network model such as a convolutional neural network (CNN) model) so that, when trained, the model can be utilized in processing vision data (e.g., from a vision component of a robot), that captures an object, to generate a rich object-centric embedding for the vision data. The generated embedding can enable differentiation of even subtle variations of attributes of the object captured by the vision data.
Public/Granted literature
- US20210334599A1 TRAINING A DEEP NEURAL NETWORK MODEL TO GENERATE RICH OBJECT-CENTRIC EMBEDDINGS OF ROBOTIC VISION DATA Public/Granted day:2021-10-28
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