SYSTEMS, APPARATUS, AND METHODS FOR EMBEDDED ENCODINGS OF CONTEXTUAL INFORMATION USING A NEURAL NETWORK WITH VECTOR SPACE MODELING
Systems, Apparatuses and Methods for implementing a neural network system for controlling an autonomous vehicle (AV) are provided, which includes: a neural network having a plurality of nodes with context to vector (context2vec) contextual embeddings to enable operations of the of the AV; a pluralit...
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Main Authors | , |
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Format | Patent |
Language | English |
Published |
13.02.2020
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Subjects | |
Online Access | Get full text |
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Summary: | Systems, Apparatuses and Methods for implementing a neural network system for controlling an autonomous vehicle (AV) are provided, which includes: a neural network having a plurality of nodes with context to vector (context2vec) contextual embeddings to enable operations of the of the AV; a plurality of encoded context2vec AV words in a sequence of timing to embed data of context and behavior; a set of inputs which comprise: at least one of a current, a prior, and a subsequent encoded context2vec AV word; a neural network solution applied by the at least one computer to determine a target context2vec AV word of each set of the inputs based on the current context2vec AV word; an output vector computed by the neural network that represents the embedded distributional one-hot scheme of the input encoded context2vec AV word; and a set of behavior control operations for controlling a behavior of the AV. |
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Bibliography: | Application Number: US201816059403 |