公开(公告)号：US20250104397A1

公开(公告)日：2025-03-27

申请号：US18904682

申请日：2024-10-02

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Hanting CHEN ,  Yunhe WANG ,  Chunjing XU

IPC: G06V10/764 ,  G06F17/16 ,  G06N3/02 ,  G06V10/77 ,  G06V10/82

Abstract: This application relates to an image recognition technology in the field of computer vision of artificial intelligence, and provides an image classification method and apparatus. An example method includes obtaining an input feature map of a to-be-processed image, and then performing feature extraction processing on the input feature map based on a feature extraction kernel of a neural network to obtain an output feature map, where each of a plurality of output sub-feature maps is determined based on the corresponding input sub-feature map and the feature extraction kernel, at least one of the output sub-feature maps is determined based on a target matrix obtained after an absolute value is taken, and a difference between the target matrix and the input sub-feature map corresponding to the target matrix is the feature extraction kernel. The to-be-processed image is classified based on the output feature map to obtain a classification result of the to-be-processed image.

公开(公告)号：US20230306719A1

公开(公告)日：2023-09-28

申请号：US18203337

申请日：2023-05-30

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Tianyu GUO ,  Hanting CHEN ,  Yunhe WANG ,  Chunjing XU

IPC: G06V10/771 ,  G06T5/50 ,  G06T7/11 ,  G06V10/44

CPC classification number: G06V10/771 ,  G06T5/50 ,  G06T7/11 ,  G06V10/44 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/20221

Abstract: Embodiments of this application disclose a model structure, a method for training a model, an image enhancement method, and a device, and may be applied to the computer vision field in the artificial intelligence field. The model structure includes: a selection module, a plurality of first neural network layers, a segmentation module, a transformer module, a recombination module, and a plurality of second neural network layers. The model overcomes a limitation that the transformer module can only be used to process a natural language task, and may be applied to a low-level vision task. The model includes the plurality of first/second neural network layers, and different first/second neural network layers correspond to different image enhancement tasks. Therefore, after being trained, the model can be used to process different image enhancement tasks.

公开(公告)号：US20250014324A1

公开(公告)日：2025-01-09

申请号：US18894274

申请日：2024-09-24

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Wenshuo LI ,  Hanting CHEN ,  Jianyuan GUO ,  Ziyang ZHANG ,  Yunhe WANG

IPC: G06V10/82 ,  G06V10/776

Abstract: An image processing method, a neural network training method, and a related device are provided. The method may apply an artificial intelligence technology to the image processing field. The method includes: performing feature extraction on a to-be-processed image by using a first neural network, to obtain feature information of the to-be-processed image. The performing feature extraction on a to-be-processed image by using a first neural network includes: obtaining first feature information corresponding to the to-be-processed image, where the to-be-processed image includes a plurality of image blocks, and the first feature information includes feature information of the image block; sequentially inputting feature information of at least two groups of image blocks into an LIF module, to obtain target data generated by the LIF module; and obtaining, based on the target data, updated feature information of the to-be-processed image including the image block.

公开(公告)号：US20240185573A1

公开(公告)日：2024-06-06

申请号：US18441229

申请日：2024-02-14

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Han SHU ,  Jiahao WANG ,  Hanting CHEN ,  Wenshuo LI ,  Yunhe WANG

IPC: G06V10/77 ,  G06V10/764 ,  G06V10/80 ,  G06V10/82

CPC classification number: G06V10/7715 ,  G06V10/764 ,  G06V10/806 ,  G06V10/82

Abstract: This disclosure provides an image classification method and a related device thereof. The method includes the following operations: After obtaining a target image, a transformer network may perform linear transformation processing based on the target image to obtain a Q-feature, a K-feature, and a V-feature. The transformer network calculates a distance between the Q-feature and the K-feature to obtain an attention feature. Then, the transformer network performs fusion processing on the attention feature and the V-feature, and obtains a classification result of the target image based on a fused feature.

公开(公告)号：US20230177641A1

公开(公告)日：2023-06-08

申请号：US18147371

申请日：2022-12-28

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Dehua SONG ,  Yunhe WANG ,  Hanting CHEN ,  Chunjing XU

IPC: G06T3/40 ,  G06T5/00 ,  G06T5/20

CPC classification number: G06T3/4046 ,  G06T3/4015 ,  G06T3/4053 ,  G06T5/003 ,  G06T5/20 ,  G06T2207/20081 ,  G06T2207/20084

Abstract: A neural network training method, includes: obtaining an input feature map of a training image; performing feature extraction processing on the input feature map by using a feature extraction core of a neural network to obtain a first candidate feature map; adding the first candidate feature map and a second candidate feature map to obtain an output feature map, where the second candidate feature map is a feature map obtained after a value corresponding to each element in the input feature map is increased by N times, and N is greater than 0; determining an image processing result of the training image based on the output feature map; and adjusting a parameter of the neural network based on the image processing result.

公开(公告)号：US20220180199A1

公开(公告)日：2022-06-09

申请号：US17680630

申请日：2022-02-25

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Yixing XU ,  Hanting CHEN ,  Kai HAN ,  Yunhe WANG ,  Chunjing XU

IPC: G06N3/08 ,  G06N3/04

Abstract: This application provides a neural network model compression method in the field of artificial intelligence. The method includes: obtaining, by a server, a first neural network model and training data of the first neural network that are uploaded by user equipment; obtaining a PU classifier based on the training data of the first neural network and unlabeled data stored in the server; selecting, by using the PU classifier, extended data from the unlabeled data stored in the server, where the extended data has a property and distribution similar to a property and distribution of the training data of the first neural network model; and training a second neural network model by using a knowledge distillation (KD) method based on the extended data, where the first neural network model is used as a teacher network model and the second neural network model is used as a student network model.

公开(公告)号：US20220157046A1

公开(公告)日：2022-05-19

申请号：US17587284

申请日：2022-01-28

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Hanting CHEN ,  Yunhe WANG ,  Chunjing XU

IPC: G06V10/764 ,  G06V10/77 ,  G06V10/82 ,  G06F17/16 ,  G06N3/02

Abstract: This application relates to an image recognition technology in the field of computer vision of artificial intelligence, and provides an image classification method and apparatus. The method includes: obtaining an input feature map of a to-be-processed image; performing feature extraction processing on the input feature map based on a feature extraction kernel of a neural network, to obtain an output feature map, where each of a plurality of output sub-feature maps is determined based on the corresponding input sub-feature map and the feature extraction kernel, at least one of the output sub-feature maps is determined based on a target matrix obtained after an absolute value is taken, and a difference between the target matrix and the input sub-feature map corresponding to the target matrix is the feature extraction kernel; and classifying the to-be-processed image based on the output feature map, to obtain a classification result of the to-be-processed image.

公开(公告)号：US20220019855A1

公开(公告)日：2022-01-20

申请号：US17488735

申请日：2021-09-29

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Hanting CHEN ,  Yunhe WANG ,  Chuanjian LIU ,  Kai HAN ,  Chunjing XU

IPC: G06K9/62 ,  G06N3/04

Abstract: The present application discloses an image generation method, a neural network compression method, and a related apparatus and device in the field of artificial intelligence. The image generation method includes: inputting a first matrix into an initial image generator to obtain a generated image; inputting the generated image into a preset discriminator to obtain a determining result, where the preset discriminator is obtained through training based on a real image and a category corresponding to the real image; updating the initial image generator based on the determining result to obtain a target image generator; and further inputting a second matrix into the target image generator to obtain a sample image. Further, a neural network compression method is disclosed, to compress the preset discriminator based on the sample image obtained by using the foregoing image generation method.