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US Patent 10339421 RGB-D scene labeling with multimodal recurrent neural networks

Patent 10339421 was granted and assigned to Toyota Motor Engineering & Manufacturing North America on July, 2019 by the United States Patent and Trademark Office.

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Is a
Patent
Patent
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Patent attributes

Patent Applicant
Toyota Motor Engineering & Manufacturing North America
Toyota Motor Engineering & Manufacturing North America
0
Current Assignee
Toyota Motor Engineering & Manufacturing North America
Toyota Motor Engineering & Manufacturing North America
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Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
103394210
Patent Inventor Names
Xue Mei0
Danil V. Prokhorov0
Haibin Ling0
Date of Patent
July 2, 2019
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Patent Application Number
154740270
Date Filed
March 30, 2017
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Patent Citations
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US Patent 10013640 Object recognition from videos using recurrent neural networks
Patent Citations Received
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US Patent 11436432 Method and apparatus for artificial neural network
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US Patent 11636681 Anticipating future video based on present video
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US Patent 11782812 Causal attention-based multi-stream RNN for computer system metric prediction and influential events identification based on metric and event logs
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US Patent 11520993 Word-overlap-based clustering cross-modal retrieval
Patent Primary Examiner
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Utpal D Shah
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Patent abstract

Described herein are systems and methods for multimodal recurrent network processing. In an embodiment, a system for evaluating multimodal data comprising a multimodal data input and a multimodal processing module is described. The multimodal data input may comprise the multimodal data, the multimodal data may comprise a first modality and a second modality. The multimodal processing module may be configured to receive the multimodal data comprising the first modality and the second modality; evaluate the first modality using a first recursive neural network comprising a first transformation matrix; evaluate the second modality using a second recursive neural network comprising the first transformation matrix; and determine an output based, at least in part, on evaluating the first modality and the second modality.

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