TRANSFORMING CONVOLUTIONAL NEURAL NETWORKS FOR VISUAL SEQUENCE LEARNING

Patent №

US 11,645,530

Granted

2023-05-09

Filed 2021

Owner

NVIDIA CORPORATION

AI components

3

ml · vision · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

17325024

A method, computer readable medium, and system are disclosed for visual sequence learning using neural networks. The method includes the steps of replacing a non-recurrent layer within a trained convolutional neural network model with a recurrent layer to produce a visual sequence learning neural network model and transforming feedforward weights for the non-recurrent layer into input-to-hidden weights of the recurrent layer to produce a transformed recurrent layer. The method also includes the steps of setting hidden-to-hidden weights of the recurrent layer to initial values and processing video image data by the visual sequence learning neural network model to generate classification or regression output data.

Machine learningVisionAI hardwareG06N 3/082G06F 18/24G06N 3/044G06N 3/0442G06N 3/045G06N 3/0464G06N 3/048G06N 3/09+3 more

AI classification

Machine learning1.00
Vision1.00
AI hardware1.00
Knowledge representation0.11
Natural language0.10
Evolutionary computation0.04
Speech0.02
Planning0.01

Ownership

NVIDIA CORPORATION

assignment · 562960080

Assignors

YANG, XIAODONG, MOLCHANOV, PAVLO, KAUTZ, JAN

On an employer assignment, the assignors are typically the inventors.

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