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1. 发明授权

US11636268B2 Generating finite state automata for recognition of organic compound names in Chinese 有权
公开(公告)号：US11636268B2
公开(公告)日：2023-04-25
申请号：US16879252
申请日：2020-05-20
申请人： FUJITSU LIMITED
发明人： Lu Fang , Zhongguang Zheng , Yingju Xia , Jun Sun
IPC分类号： G06F40/289 , G06N5/04 , G06N20/00
摘要： The present disclosure relates to a method and device for generating a finite state automata for recognizing a chemical name in a text, and a recognition method. According to an embodiment of the present disclosure, the method comprises substituting representation constants of categories of character segments appearing in an organic compound name set into the organic compound name set to obtain a conversion name set; updating the conversion name set based on a conversion name segment which repeatedly appears in the conversion name set; and generating the finite state automata based on the updated conversion name set.

2. 发明授权

US11556735B2 Training device and training method for training multi-goal model 有权
公开(公告)号：US11556735B2
公开(公告)日：2023-01-17
申请号：US16868860
申请日：2020-05-07
申请人： FUJITSU LIMITED
发明人： Chaoliang Zhong , Wensheng Xia , Ziqiang Shi , Jun Sun
IPC分类号： G06K9/62 , G06N20/00
摘要： A training device and a training method for training a multi-goal model based on goals in a goal space are provided. The training device includes a memory and a processor coupled to the memory. The processor is configured to set the goal space, to acquire a plurality of sub-goal spaces of different levels of difficulty; change a sub-goal space to be processed from a current sub-goal space to a next sub-goal space of a higher level of difficulty; select, as sampling goals, goals at least from the current sub-goal space, and to acquire transitions related to the sampling goals by executing actions; train the multi-goal model based on the transitions, and evaluate the multi-goal model by calculating a success rate for achieving goals in the current sub-goal space.

3. 发明申请

US20210073470A1 METHOD AND DEVICE FOR GENERATING FINITE STATE AUTOMATA, AND RECOGNITION METHOD 有权
公开(公告)号：US20210073470A1
公开(公告)日：2021-03-11
申请号：US16879252
申请日：2020-05-20
申请人： FUJITSU LIMITED
发明人： Lu Fang , Zhongguang Zheng , Yingju Xia , Jun Sun
IPC分类号： G06F40/289 , G06N20/00 , G06N5/04
摘要： The present disclosure relates to a method and device for generating a finite state automata for recognizing a chemical name in a text, and a recognition method. According to an embodiment of the present disclosure, the method comprises substituting representation constants of categories of character segments appearing in an organic compound name set into the organic compound name set to obtain a conversion name set; updating the conversion name set based on a conversion name segment which repeatedly appears in the conversion name set; and generating the finite state automata based on the updated conversion name set.

4. 发明授权

US10296813B2 Training method and apparatus for neural network for image recognition 有权
公开(公告)号：US10296813B2
公开(公告)日：2019-05-21
申请号：US15254249
申请日：2016-09-01
申请人： FUJITSU LIMITED
发明人： Li Chen , Song Wang , Wei Fan , Jun Sun , Naoi Satoshi
IPC分类号： G06K9/62 , G06T5/20 , G06N3/08
摘要： A training method and a training apparatus for a neutral network for image recognition are provided. The method includes: representing a sample image as a point set in a high-dimensional space, a size of the high-dimensional space being a size of space domain of the sample image multiplied by a size of intensity domain of the sample image; generating a first random perturbation matrix having a same size as the high-dimensional space; smoothing the first random perturbation matrix; perturbing the point set in the high-dimensional space using the smoothed first random perturbation matrix to obtain a perturbed point set; and training the neutral network using the perturbed point set as a new sample. With the training method and the training apparatus, classification performance of a conventional convolutional neural network is improved, thereby generating more training samples, reducing influence of overfitting, and enhancing generalization performance of the convolutional neural network.

5. 发明授权

US09256782B2 Apparatus and method for processing document image to estimate luminance image from luminance component image adjusted according to estimated or largest luminance values and predetermined criterion 有权
标题翻译：用于处理文档图像以根据估计或最大亮度值和预定标准调整的亮度分量图像来估计亮度图像的装置和方法
公开(公告)号：US09256782B2
公开(公告)日：2016-02-09
申请号：US14613710
申请日：2015-02-04
申请人： FUJITSU LIMITED
发明人： Pan Pan , Yuan He , Jun Sun
IPC分类号： H04N1/407 , H04N1/409 , G06T5/00 , G06K9/00
CPC分类号： G06K9/00442 , G06K9/2027 , G06T5/00 , G06T5/008 , H04N1/407 , H04N1/4072
摘要： An apparatus for and a method of processing a document image are provided. The method comprises: generating a luminance component image from the document image; estimating a luminance image from the luminance component image; and adjusting the luminance component image according to the estimated luminance image. Luminance values of pixels at least in horizontal edge areas of the luminance component image are estimated according to luminance values of pixels in a part of background of the luminance component image. If the estimated luminance values are acceptable according to a predetermined criterion, the luminance image is estimated according to the estimated luminance values. If the estimated luminance values are unacceptable, the luminance image is estimated by using the largest one of the luminance values of the pixels in each column of pixels in the luminance component image as the luminance values of all of the pixels in the column.
摘要翻译：提供了一种用于处理文档图像的装置和方法。该方法包括：从文档图像生成亮度分量图像; 从亮度分量图像估计亮度图像; 以及根据所估计的亮度图像来调整亮度分量图像。至少在亮度分量图像的水平边缘区域中的像素的亮度值根据亮度分量图像的背景的一部分中的像素的亮度值来估计。如果根据预定标准估计的亮度值是可接受的，则根据估计的亮度值来估计亮度图像。如果估计的亮度值不可接受，则通过使用亮度分量图像中的每列像素中的像素的亮度值中的最大的一个来估计亮度图像作为列中所有像素的亮度值。

6. 发明授权

US09202282B2 Boundary extraction method and apparatus 有权
标题翻译：边界提取方法和装置
公开(公告)号：US09202282B2
公开(公告)日：2015-12-01
申请号：US13906001
申请日：2013-05-30
申请人： FUJITSU LIMITED
发明人： Yuan He , Jun Sun , Satoshi Naoi
IPC分类号： G06T7/00 , G06T5/00 , G06T5/20
CPC分类号： G06T7/0085 , G06T5/003 , G06T5/20 , G06T7/12 , G06T7/181 , G06T2207/10008 , G06T2207/20192 , G06T2207/30176
摘要： The present invention discloses a boundary extraction method and apparatus, the method including: a gradient estimation step of estimating a gradient of each pixel in a captured image; a gradient adjustment step of adjusting, by enhancing a gradient of a target boundary of an object contained in the captured image and weakening a gradient of a noise boundary, the estimated gradient, so that the adjusted gradient is considered as a current gradient; and a boundary extraction step of extracting a boundary of the object based on the current gradient. According to the embodiments of the invention, in a case of using a non-contact imaging device to capture an image, it is possible to more accurately extract a boundary of an object contained in the captured image.
摘要翻译：本发明公开了一种边界提取方法和装置，该方法包括：估计拍摄图像中每个像素的梯度的梯度估计步骤; 梯度调整步骤，通过增强包含在所捕获的图像中的对象的目标边界的梯度并减弱噪声边界的梯度来估计所述估计的梯度，从而将所述调整的梯度视为当前梯度; 以及边界提取步骤，基于当前梯度提取对象的边界。根据本发明的实施例，在使用非接触式成像装置拍摄图像的情况下，可以更准确地提取包含在拍摄图像中的对象的边界。

7. 发明申请

US20130330009A1 APPARATUS, METHOD FOR EXTRACTING BOUNDARY OF OBJECT IN IMAGE, AND ELECTRONIC DEVICE THEREOF 有权
标题翻译：装置，提取图像中对象边界的方法及其电子装置
公开(公告)号：US20130330009A1
公开(公告)日：2013-12-12
申请号：US13912805
申请日：2013-06-07
申请人： FUJITSU LIMITED
发明人： Pan PAN , Yuan He , Jun Sun , Satoshi Naoi
IPC分类号： G06T7/00
CPC分类号： G06T7/0085 , G06T7/12
摘要： The invention provides an apparatus and method for extracting a boundary of an object in an image and an electronic device. The apparatus includes: a position determining unit, configured to determine a start point and an end point of a boundary of an object in an image and to determine a position of a reference point relevant to the start point and the end point; a first direction determining unit, configured to determine a first direction of the boundary; a gradient map obtaining unit, configured to obtain a gradient map of a first region; a gradient attenuating unit, configured to attenuate in the gradient map the gradients of a second region; and an extracting unit, configured to extract a boundary of an object. The technology of the invention can improve the accuracy of boundary extracting, and can be applied in the field of image processing.
摘要翻译：本发明提供一种用于提取图像和电子设备中的对象的边界的装置和方法。该装置包括：位置确定单元，被配置为确定图像中的对象的边界的起始点和终点，并确定与开始点和终点相关的参考点的位置; 第一方向确定单元，被配置为确定所述边界的第一方向; 梯度图获取单元，被配置为获得第一区域的梯度图; 梯度衰减单元，被配置为在梯度图中衰减映射第二区域的梯度; 以及提取单元，被配置为提取对象的边界。本发明的技术可以提高边界提取的准确性，可以应用于图像处理领域。

8. 发明授权

US11049017B2 Device and method for determining convolutional neural network model 有权
公开(公告)号：US11049017B2
公开(公告)日：2021-06-29
申请号：US15723457
申请日：2017-10-03
申请人： FUJITSU LIMITED
发明人： Li Sun , Song Wang , Wei Fan , Jun Sun
IPC分类号： G06N3/08 , G06N3/10 , G06N3/04
摘要： Provided are device and method for determining a Convolutional Neural Network (CNN) model. The device for determining the CNN model includes: a first determination unit configured to determine complexity of a database including multiple samples; a second determination unit configured to determine a classification capability of a CNN model applicable to the database based on the complexity of the database; a third determination unit configured to acquire classification capability of each candidate CNN model; and a matching unit configured to determine the CNN model applicable to the database based on the classification capability of each candidate CNN model. With the device and method for determining the CNN module, a design process of CNN model can be simplified.

9. 发明授权

US10902296B2 Method and apparatus for training classification model, method and apparatus for classifying 有权
公开(公告)号：US10902296B2
公开(公告)日：2021-01-26
申请号：US16445240
申请日：2019-06-19
申请人： FUJITSU LIMITED
发明人： Zhanzhong Pang , Xiaoyi Yu , Jun Sun
IPC分类号： G06K9/62 , G06K9/46
摘要： Disclosed are a method and apparatus for training a classification model and a method and apparatus for classifying. A method for classifying comprises: extracting a feature from to-be-tested information inputted to a classification model having been trained; compressing the extracted feature into a low dimensional hidden feature capable of representing the to-be-tested information; performing decompression on the hidden feature to obtain a decompressed feature; performing rebuilding on the to-be-tested information based on the decompressed feature, to obtain reconstructed to-be-tested information; judging, based on a rebuild loss between the to-be-tested information and the reconstructed to-be-tested information, whether the to-be-tested information belongs to a known class or an unknown class; and performing classification on the to-be-tested information, via the classification model having been trained, in a case where it is determined that the to-be-tested information belongs to a known class.

10. 发明申请

US20190147336A1 METHOD AND APPARATUS OF OPEN SET RECOGNITION AND A COMPUTER READABLE STORAGE MEDIUM 审中-公开
公开(公告)号：US20190147336A1
公开(公告)日：2019-05-16
申请号：US16180400
申请日：2018-11-05
申请人： FUJITSU LIMITED
发明人： Xiaoyi YU , Jun Sun
IPC分类号： G06N3/08 , G06K9/62 , G06N5/04 , G06N3/04
摘要： A method and apparatus of open set recognition, and a computer-readable storage medium are disclosed. The method comprises acquiring auxiliary data and training data of known categories for open set recognition, training a neural network alternately using the auxiliary data and the training data, until convergence; extracting a feature of data to be recognized for open set recognition, using the trained neural network; and recognizing a category of data to be recognized, based on the feature of the data to be recognized.

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