-
公开(公告)号：US11328179B2
公开(公告)日：2022-05-10
申请号：US16910245
申请日：2020-06-24
Applicant: FUJITSU LIMITED
IPC: G06K9/62 , G06N3/08 , G06V10/40 , G06V30/194
Abstract: An information processing apparatus includes a processor to input each sample image into feature extracting components to obtain at least two features of the sample image, and to cause a classifying component to calculate a classification loss of the sample image based on the at least two features; extract, from each pair of features, a plurality of sample pairs for calculating mutual information between each pair of features; input the plurality of sample pairs into a machine learning architecture corresponding to each pair of features, to calculate an information loss between each pair of features. The processor is to adjust parameters of the feature extracting components, the classifying component and the machine learning architecture by minimizing a sum of classification losses and information losses of sample images in the training set based upon the obtained at least two features of the sample image to calculate the classification losses and the information losses, to obtain the at least two feature extracting components and the classifying component having been trained.
-
公开(公告)号：US11113581B2
公开(公告)日：2021-09-07
申请号：US16450153
申请日：2019-06-24
Applicant: FUJITSU LIMITED
Inventor： Meng Zhang , Rujie Liu
Abstract: The present disclosure relates to an information processing method and an information processing apparatus. The information processing method according to the present disclosure performs training on a classification model by using a plurality of training samples, and comprises the steps of: adjusting a distribution of feature vectors of the plurality of training samples in a feature space based on a typical sample in the plurality of training samples; and performing training on the classification model by using the adjusted feature vectors of the plurality of training samples. Through the technology according to the present disclosure, it is possible to perform pre-adjustment on training samples before training, such that it is possible to reduce discrimination between training samples belonging to a same class and increase discrimination between training samples belonging to different classes in the training process. The classification model trained as such is capable of performing accurate classification on samples acquired under an extreme condition.
-
公开(公告)号：US20210166119A1
公开(公告)日：2021-06-03
申请号：US17102722
申请日：2020-11-24
Applicant: FUJITSU LIMITED
Inventor： Mengjiao Wang , Rujie Liu
Abstract: The present disclosure relates to an information processing method and an information processing apparatus. The information processing apparatus according to the present disclosure comprises: a determining unit configured to respectively determine a discrimination margin of each class of a plurality of classes of a training sample set containing the plurality of classes relative to other classes; and a training unit configured to use, based on the determined discrimination margin, the training sample set for training a classifying model. By the information processing apparatus and the information processing method according to the present disclosure, a classifying model can be trained by using a training sample set of which training samples are distributed unevenly, so that a classifying model capable of performing accurate classification can be obtained without significantly increasing a calculation cost.
-
公开(公告)号：US10990853B2
公开(公告)日：2021-04-27
申请号：US16191090
申请日：2018-11-14
Applicant: FUJITSU LIMITED
Inventor： Mengjiao Wang , Rujie Liu
IPC: G06K9/62
Abstract: An information processing method and an information processing apparatus are disclosed, where the information processing method includes: inputting a plurality of samples to a classifier respectively, to extract a feature vector representing a feature of each sample; and updating parameters of the classifier by minimizing a loss function for the plurality of samples, wherein the loss function is in positive correlation with an intra-class distance for representing a distance between feature vectors of samples belonging to a same class, and is in negative correlation with an inter-class distance for representing a distance between feature vectors of samples belonging to different classes, wherein the intra-class distance of each sample of the plurality of samples is less than a first threshold, the inter-class distance between two different classes is greater than a second threshold, and the second threshold is greater than twice the first threshold.
-
Patent Agency Ranking
公开(公告)号：US10885308B2
公开(公告)日：2021-01-05
申请号：US16159031
申请日：2018-10-12
Applicant: FUJITSU LIMITED
Inventor： Pingping Lu , Rujie Liu
Abstract: A method and apparatus for evaluating an illumination condition in a face image is provided by decomposing a face image into illumination feature components and face feature components; extracting determined areas in the face image; calculating a maximum luminance feature, a minimum luminance feature and an illumination direction feature according to the decomposed illumination feature components in the determined areas. The illumination condition in the face image is evaluated according to the maximum luminance feature, the minimum luminance feature and the illumination direction feature.
-
36.发明申请公开(公告)号：US20200265220A1
公开(公告)日：2020-08-20
申请号：US16738393
申请日：2020-01-09
Applicant: FUJITSU LIMITED
Inventor： Meng Zhang , Rujie Liu
Abstract: An apparatus and method for training a classification model and an apparatus for classifying with a classification model are disclosed. The apparatus for training a classification model comprises: a local area obtainment unit to, obtain predetermined local area of each sample image; a feature extraction unit to, with respect to each sample image, set corresponding numbers of feature extraction layers for the global area and each predetermined local area, to extract a global feature of the global area and a local feature of each predetermined local area, wherein the global area and the predetermined local areas share at least one feature extraction layer in which the global feature and each local feature are combined; and a loss determination unit to calculate a loss function of the sample image based on combined features of each sample image, and to train the classification model based on the loss function.
-
公开(公告)号：USRE47340E1
公开(公告)日：2019-04-09
申请号：US14700894
申请日：2015-04-30
Applicant: FUJITSU LIMITED
Inventor： Rujie Liu , Takayuki Baba , Susumu Endo , Shuichi Shiitani , Yusuke Uehara , Daiki Masumoto , Shigemi Nagata
Abstract: This invention discloses an image retrieval apparatus. The image retrieval apparatus comprises an unlabelled image selector for selecting one or more unlabelled image(s) from an image database; and a main learner for training in each feedback round of the image retrieval, estimating relevance of images in the image database and a user's intention, and determining retrieval results, wherein the main learner makes use of the unlabelled image(s) selected by the unlabelled image selector in the estimation. In addition, the image retrieval apparatus may also include an active selector for selecting, in each feedback round and according to estimation results of the main learner, one or more unlabelled image(s) from the image database for the user to label.
-
公开(公告)号：US20180173997A1
公开(公告)日：2018-06-21
申请号：US15843719
申请日：2017-12-15
Applicant: Fujitsu Limited
IPC: G06K9/62
CPC classification number: G06K9/6256 , G06K9/00281 , G06K9/6227 , G06K9/6262 , G06K9/628 , G06N3/0454 , G06N3/088
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.
-
公开(公告)号：US20180158186A1
公开(公告)日：2018-06-07
申请号：US15816315
申请日：2017-11-17
Applicant: Fujitsu Limited
Inventor： Mengjiao Wang , Rujie Liu
CPC classification number: G06T7/0016 , G06K9/4642 , G06K9/6212 , G06K9/6215 , G06K2009/6213 , G06T7/0014 , G06T7/11 , G06T7/13 , G06T7/136 , G06T2207/10072 , G06T2207/20021 , G06T2207/30012 , G06T2207/30061
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.
-
-
-
-
-
-
-
-
Search Results
39
records
(took 0.023 seconds)
