Method and device with video conversion
AssigneeSamsung Electronics Co., Ltd.
InventorsHyoa KANG, Hee Min CHOI
Life of this patent
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Abstract
A processor-implemented method includes: initializing a neural network model with arbitrary values using a random seed; training the neural network model based on the arbitrary values; determining a number of coats and respective densities of the coats; learning respective scores of parameters of the neural network model based on the number of coats and the respective densities of the coats; determining mask information for determining the parameters of the neural network model to be comprised in each of the coats based on the scores; and generating a bitstream based on the number of coats, the respective densities of the coats, the mask information, and the random seed.
Claims20
A processor-implemented method comprising:
- initializing a neural network model with arbitrary values using a random seed;
- training the neural network model based on the arbitrary values;
- determining a number of coats and respective densities of the coats;
- learning respective scores of parameters of the neural network model based on the number of coats and the respective densities of the coats;
- determining mask information for determining the parameters of the neural network model to be comprised in each of the coats based on the scores;
- and
- generating a bitstream based on the number of coats, the respective densities of the coats, the mask information, and the random seed.
A processor-implemented method comprising:
- receiving a bitstream;
- obtaining a random seed, a number of coats, respective densities of the coats, and mask information by decoding the received bitstream;
- initializing a neural network model using the random seed;
- determining a number of coats and respective densities of coats to be used in the neural network model based on constraints on an amount of computation;
- based on the determined number of coats and the determined respective densities of the coats, determining scale information corresponding to the determined coats;
- and
- generating parameters of the neural network model based on the scale information and the mask information.
An electronic device comprising:
- one or more processors configured to:
- initialize a neural network model with arbitrary values using a random seed;
- train the neural network model based on the arbitrary values;
- determine a number of coats and respective densities of the coats;
- learn respective scores of parameters of the neural network model based on the number of coats and the respective densities of the coats and determine mask information for determining the parameters of the neural network model to be comprised in each of the coats based on the scores;
- and
- generate a bitstream based on the number of coats, the respective densities of the coats, the mask information, and the random seed.
Dependencies are inferred from the claim text.