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US Patent 11983630 Neural networks for embedded devices

Patent 11983630 was granted and assigned to Tesla, Inc. on May, 2024 by the United States Patent and Trademark Office.

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Is a
Patent
Patent
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Patent attributes

Patent Applicant
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Tesla, Inc.
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Current Assignee
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Tesla, Inc.
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Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
119836300
Patent Inventor Names
Yiqi Hou0
Forrest Nelson Iandola0
Harsimran Singh Sidhu0
Date of Patent
May 14, 2024
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Patent Application Number
181566280
Date Filed
January 19, 2023
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Patent Citations
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US Patent 8165380 Method, apparatus and program for processing mammographic image
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US Patent 8369633 Video codec method and system
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US Patent 8406515 Method for automatically cropping digital images
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US Patent 8509478 Detection of objects in digital images
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US Patent 8588470 Methods and systems for improved license plate signature matching by similarity learning on synthetic images
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US Patent 8744174 Image processing apparatus, image processing method, and storage medium
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Patent Primary Examiner
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Steven G Snyder
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Patent abstract

A neural network architecture is used that reduces the processing load of implementing the neural network. This network architecture may thus be used for reduced-bit processing devices. The architecture may limit the number of bits used for processing and reduce processing to prevent data overflow at individual calculations of the neural network. To implement this architecture, the number of bits used to represent inputs at levels of the network and the related filter masks may also be modified to ensure the number of bits of the output does not overflow the resulting capacity of the reduced-bit processor. To additionally reduce the load for such a network, the network may implement a “starconv” structure that permits the incorporation of nearby nodes in a layer to balance processing requirements and permit the network to learn from context of other nodes.

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