公开(公告)号：US20250080768A1

公开(公告)日：2025-03-06

申请号：US18950354

申请日：2024-11-18

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Alexander Nikolaevich FILIPPOV ,  Kirill Igorevich SOLODSKIKH ,  Vladimir Maximovich CHIKIN ,  Dehua SONG ,  Stanislav Yuryevich KAMENEV ,  Irina ZHELAVSKAYA

IPC: H04N19/48 ,  H04N9/69 ,  H04N19/124

Abstract: Embodiments of this application provide a method method for transforming data and a related device. The method includes: obtaining an input image, wherein the input image includes N pixels, Nis a positive integer; performing a nonlinear transformation on values of the N pixels to obtain N first pixel values; obtaining, according to a quantized model and the N first pixel values, M second pixel values, wherein M is a positive integer; performing a reverse transformation corresponding to the nonlinear transformation on the M second pixel values to obtain M third pixel values; determining, according to the M third pixels values, an output image.

公开(公告)号：US20230037498A1

公开(公告)日：2023-02-09

申请号：US17969358

申请日：2022-10-19

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Vladimir Mikhailovich KRYZHANOVSKIY ,  Nikolay Mikhailovich KOZYRSKIY ,  Stanislav Yuryevich KAMENEV ,  Alexander Alexandrovich ZURUEV

IPC: G06K9/62

Abstract: A method for generating a predictive model for quantization parameters of a neural network is described. The method comprises accessing a first vector of data values corresponding to input values to a first layer implemented in a neural network, generating a feature vector of one or more features extracted from the data values of the first vector, accessing a second vector of data values corresponding to the input values of a second layer implemented in the neural network, subsequent to the first layer, generating a target vector of data values comprising one or more quantization parameters for the second layer, from the data values of the second vector, evaluating, on the basis of the feature vector and the target vector, a predictive model for predicting the one or more quantization parameters of the second layer and modifying the predictive model on the basis of the evaluation.