公开(公告)号：US20210142179A1

公开(公告)日：2021-05-13

申请号：US17090071

申请日：2020-11-05

Applicant: Intel Corporation

Inventor： Xiaoming Chen ,  Anbang Yao ,  Junjie Huang ,  Tao Lv ,  Yuanke Luo

IPC: G06N3/08 ,  G06N3/04 ,  G06N3/063 ,  G06N20/10

Abstract: Embodiments are generally directed to dynamically dividing activations and kernels for improving memory efficiency. An embodiment of a method in a compute engine performing machine learning comprises: receiving, by a convolutional layer of a convolutional neural network (CNN) implemented on the compute engine, a plurality of activation groups contained in an input data, wherein the convolutional layer includes one or more kernel groups and the one or more kernel groups each include a plurality of kernels; determining a plurality of memory efficiency metrics based on the number of activation groups of the plurality of activation groups and the number of kernels of the plurality of kernels; selecting a first optimal number of activation groups and a second optimal number of kernels that are associated with an optimal memory efficiency metric in the plurality of memory efficiency metrics; and performing a convolutional operation on the input data based on the first optimal number and the second optimal number.

公开(公告)号：US11869171B2

公开(公告)日：2024-01-09

申请号：US17090170

申请日：2020-11-05

Applicant: Intel Corporation

Inventor： Anbang Yao ,  Ming Lu ,  Yikai Wang ,  Xiaoming Chen ,  Junjie Huang ,  Tao Lv ,  Yuanke Luo ,  Yi Yang ,  Feng Chen ,  Zhiming Wang ,  Zhiqiao Zheng ,  Shandong Wang

IPC: G06T5/00 ,  G06N3/04

CPC classification number: G06T5/002 ,  G06N3/04 ,  G06T2207/20081 ,  G06T2207/20084

Abstract: Embodiments are generally directed to an adaptive deformable kernel prediction network for image de-noising. An embodiment of a method for de-noising an image by a convolutional neural network implemented on a compute engine, the image including a plurality of pixels, the method comprising: for each of the plurality of pixels of the image, generating a convolutional kernel having a plurality of kernel values for the pixel; generating a plurality of offsets for the pixel respectively corresponding to the plurality of kernel values, each of the plurality of offsets to indicate a deviation from a pixel position of the pixel; determining a plurality of deviated pixel positions based on the pixel position of the pixel and the plurality of offsets; and filtering the pixel with the convolutional kernel and pixel values of the plurality of deviated pixel positions to obtain a de-noised pixel.

公开(公告)号：US20240127408A1

公开(公告)日：2024-04-18

申请号：US18514252

申请日：2023-11-20

Applicant: Intel Corporation

Inventor： Anbang Yao ,  Ming Lu ,  Yikai Wang ,  Xiaoming Chen ,  Junjie Huang ,  Tao Lv ,  Yuanke Luo ,  Yi Yang ,  Feng Chen ,  Zhiming Wang ,  Zhiqiao Zheng ,  Shandong Wang

IPC: G06T5/00 ,  G06N3/04

CPC classification number: G06T5/002 ,  G06N3/04 ,  G06T2207/20081 ,  G06T2207/20084

Abstract: Embodiments are generally directed to an adaptive deformable kernel prediction network for image de-noising. An embodiment of a method for de-noising an image by a convolutional neural network implemented on a compute engine, the image including a plurality of pixels, the method comprising: for each of the plurality of pixels of the image, generating a convolutional kernel having a plurality of kernel values for the pixel; generating a plurality of offsets for the pixel respectively corresponding to the plurality of kernel values, each of the plurality of offsets to indicate a deviation from a pixel position of the pixel; determining a plurality of deviated pixel positions based on the pixel position of the pixel and the plurality of offsets; and filtering the pixel with the convolutional kernel and pixel values of the plurality of deviated pixel positions to obtain a de-noised pixel.

公开(公告)号：US20210142448A1

公开(公告)日：2021-05-13

申请号：US17090170

申请日：2020-11-05

Applicant: Intel Corporation

Inventor： Anbang Yao ,  Ming Lu ,  Yikai Wang ,  Xiaoming Chen ,  Junjie Huang ,  Tao Lv ,  Yuanke Luo ,  Yi Yang ,  Feng Chen ,  Zhiming Wang ,  Zhiqiao Zheng ,  Shandong Wang

IPC: G06T5/00 ,  G06N3/04

Abstract: Embodiments are generally directed to an adaptive deformable kernel prediction network for image de-noising. An embodiment of a method for de-noising an image by a convolutional neural network implemented on a compute engine, the image including a plurality of pixels, the method comprising: for each of the plurality of pixels of the image, generating a convolutional kernel having a plurality of kernel values for the pixel; generating a plurality of offsets for the pixel respectively corresponding to the plurality of kernel values, each of the plurality of offsets to indicate a deviation from a pixel position of the pixel; determining a plurality of deviated pixel positions based on the pixel position of the pixel and the plurality of offsets; and filtering the pixel with the convolutional kernel and pixel values of the plurality of deviated pixel positions to obtain a de-noised pixel.