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1.发明授权公开(公告)号：US11790046B2
公开(公告)日：2023-10-17
申请号：US17460316
申请日：2021-08-30
Applicant: FUJITSU LIMITED
Inventor： Meng Zhang , Rujie Liu
IPC: G06F18/2413 , G06V40/16 , G06F18/214
CPC classification number: G06F18/2413 , G06F18/214 , G06V40/168 , G06V40/172
Abstract: A device and a method for classification using a pre-trained classification model and a computer readable storage medium are provided. The device is configured to extract, for each of multiple images in a target image group to be classified, a feature of the image using a feature extraction layer of the pre-trained classification model; calculate, for each of the multiple images, a contribution of the image to a classification result of the target image group using a contribution calculation layer of the pre-trained classification model; aggregate extracted features of the multiple images based on calculated contributions of the multiple images, to obtain an aggregated feature as a feature of the target image group; and classify the target image group based on the feature of the target image group.
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公开(公告)号：US20200265308A1
公开(公告)日：2020-08-20
申请号：US16748107
申请日：2020-01-21
Applicant: FUJITSU LIMITED
Inventor： Mengjiao Wang , Rujie Liu
Abstract: The present disclosure relates to a model optimization method, a data identification method and a data identification device. A method for optimizing a data identification model comprises: acquiring a loss function of a data identification model to be optimized; calculating weight vectors in the loss function which correspond to classes; performing normalization processing on the weight vectors; updating the loss function by increasing an included angle between any two of the weight vectors; optimizing the data identification model to be optimized based on the updated loss function.
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公开(公告)号：US10552712B2
公开(公告)日：2020-02-04
申请号：US15843719
申请日：2017-12-15
Applicant: Fujitsu Limited
Abstract: The disclosure relates to a training device and method for an image processing device and an image processing device. The training device is used for training first and second image processing units, comprising: a training unit to input a first realistic image without a specific feature into the first image processing unit to generate a first generated image with the specific feature through first image processing, and to input a second realistic image with the specific feature into the second image processing unit to generate a second generated image without the specific feature through second image processing; and a classifying unit performing classification processing to discriminate realistic and generated images, wherein the training unit performs first training processing of training the classifying unit based on the realistic and generated images, and performs second training processing of training the first and second image processing units based on the training result.
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公开(公告)号：US20190122394A1
公开(公告)日：2019-04-25
申请号：US16136940
申请日：2018-09-20
Applicant: FUJITSU LIMITED
Abstract: An image processing apparatus and an image processing method where the apparatus includes: a self-encoder configured to perform self-encoding on an input image to generate multiple feature maps; a parameter generator configured to generate multiple convolution kernels for a convolution neural network based on the multiple feature maps; and an outputter configured to generate, by using the convolution neural network, an output result of the input image based on the input image and the multiple convolution kernels. With the image processing apparatus and the image processing method according to the present disclosure, an accuracy of processing an image by using the CNN network can be improved.
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公开(公告)号：US11514264B2
公开(公告)日：2022-11-29
申请号：US17076320
申请日：2020-10-21
Applicant: FUJITSU LIMITED
Inventor： Meng Zhang , Fei Li , Rujie Liu
Abstract: A method for training a classification model includes: performing training on the classification model using first and second sample sets, to calculate a classification loss; extracting a weight vector and a feature vector of each sample; calculating a mean weight vector and a mean feature vector of all samples in the first sample set; calculating a weight loss based on a difference of the weight vector of each sample in the second sample set from the mean weight vector, and calculating a feature loss based on a difference of a feature vector of each sample in the second sample set from the mean feature vector; calculating a total loss of the classification model based on the classification loss and at least one of the feature loss and the weight loss; and adjusting a parameter of the classification model until a predetermined condition is satisfied.
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Patent Agency Ranking
公开(公告)号：US20210150261A1
公开(公告)日：2021-05-20
申请号：US17076320
申请日：2020-10-21
Applicant: FUJITSU LIMITED
Inventor： Meng Zhang , Fei Li , Rujie Liu
Abstract: A method for training a classification model includes: performing training on the classification model using first and second sample sets, to calculate a classification loss; extracting a weight vector and a feature vector of each sample; calculating a mean weight vector and a mean feature vector of all samples in the first sample set; calculating a weight loss based on a difference of the weight vector of each sample in the second sample set from the mean weight vector, and calculating a feature loss based on a difference of a feature vector of each sample in the second sample set from the mean feature vector; calculating a total loss of the classification model based on the classification loss and at least one of the feature loss and the weight loss; and adjusting a parameter of the classification model until a predetermined condition is satisfied.
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公开(公告)号：US10776918B2
公开(公告)日：2020-09-15
申请号：US15816315
申请日：2017-11-17
Applicant: Fujitsu Limited
Inventor： Mengjiao Wang , Rujie Liu
Abstract: The present application relates to method and device for determining image similarity that includes: dividing a target image into multiple regions based on positions of pixels relative to a reference point in the target image, and dividing a reference image into multiple regions based on positions of pixels relative to a reference point in the reference image; determining, based on feature points in the target image and feature points in the reference image as well as the regions obtained by dividing the target image and the regions obtained by dividing the reference image, similarity between a distribution of the feature points in the target image and a distribution of the feature points in the reference image. According to the method of the present application, the similarity is described more reasonably.
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公开(公告)号：US10769499B2
公开(公告)日：2020-09-08
申请号：US16179292
申请日：2018-11-02
Applicant: FUJITSU LIMITED
Inventor： Meng Zhang , Rujie Liu , Jun Sun
Abstract: A method and apparatus for removing black eyepits and sunglasses in first actual scenario data having an image containing a face acquired from an actual scenario, to obtain second actual scenario data; counting a proportion of wearing glasses in the second actual scenario data; dividing original training data composed of an image containing a face into wearing-glasses and not-wearing-glasses first and second training data, where a proportion of wearing glasses in the original training data is lower than a proportion in the second actual scenario data; generating wearing-glasses third training data based on glasses data and the second training data; generating fourth training data in which a proportion of wearing glasses is equal to the proportion of wearing glasses in the second actual scenario data, based on the third training data and the original training data; and training a face recognition model based on the fourth training data.
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公开(公告)号：US10410345B2
公开(公告)日：2019-09-10
申请号：US15827570
申请日：2017-11-30
Applicant: Fujitsu Limited
Inventor： Mengjiao Wang , Rujie Liu
Abstract: An image processing device and an image processing method are provided. The image processing device includes: an acquisitor configured to acquire multiple slice images arranged in an order; a selector configured to detect the multiple slice images sequentially, to determine a reference slice image and a reference trachea region in the reference slice image; and a branch point determiner configured to determine, with a region growing method, trachea regions of slice images following the reference slice image sequentially by using the reference trachea region as a seed region, and determine connectivity of the trachea regions, until a branch point slice image is determined, where a trachea region of the branch point slice image includes two disconnected regions. With the image processing device and the image processing method, manual intervention can be reduced and a position of the branch point can be determined more accurately.
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公开(公告)号：US20180240232A1
公开(公告)日：2018-08-23
申请号：US15827570
申请日：2017-11-30
Applicant: Fujitsu Limited
Inventor： Mengjiao WANG , Rujie Liu
CPC classification number: G06T7/0012 , G06T7/11 , G06T7/174 , G06T7/187 , G06T2207/10081 , G06T2207/20156 , G06T2207/30061
Abstract: An image processing device and an image processing method are provided. The image processing device includes: an acquisitor configured to acquire multiple slice images arranged in an order; a selector configured to detect the multiple slice images sequentially, to determine a reference slice image and a reference trachea region in the reference slice image; and a branch point determiner configured to determine, with a region growing method, trachea regions of slice images following the reference slice image sequentially by using the reference trachea region as a seed region, and determine connectivity of the trachea regions, until a branch point slice image is determined, where a trachea region of the branch point slice image includes two disconnected regions. With the image processing device and the image processing method, manual intervention can be reduced and a position of the branch point can be determined more accurately.
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