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1. 发明申请

US20180130140A1 SOCIAL RELATIONSHIP CHAIN OBTAINING METHOD AND TERMINAL AND STORAGE MEDIUM 审中-公开
公开(公告)号：US20180130140A1
公开(公告)日：2018-05-10
申请号：US15861358
申请日：2018-01-03
申请人： Dalian Minzu University , TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED
发明人： Xiaoke XU , Yading YUE , Peng HE , Chuan CHEN , Tingting LIU , Jia LIU
IPC分类号： G06Q50/00 , G06F17/30 , H04L29/08
CPC分类号： G06Q50/01 , G06F16/95 , H04L29/08 , H04L67/306
摘要： Social relationship chain obtaining method and terminal and a readable medium are provided. The method includes: obtaining a target user set and mutual-friend information between any two target users in the target user set, target users in the target user set being friends of a center user, and the mutual-friend information indicating whether the two target users are in a friend relationship; constructing a reference network according to the center user and the mutual-friend information between the any two target users in the target user set, nodes in the reference network being the target users in the target user set, and there being a connection line between two target users in the reference network that are in a friend relationship; and determining, from the target user set according to the reference network, a target user being in a parent-child relationship chain with the center user.

2. 发明申请

US20180165511A1 THREE-DIMENSIONAL FACIAL RECOGNITION METHOD AND SYSTEM 审中-公开
公开(公告)号：US20180165511A1
公开(公告)日：2018-06-14
申请号：US15822853
申请日：2017-11-27
申请人： Beijing University of Posts and Telecommunications , TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED
发明人： Yue MING , Jie JIANG , Tingting LIU , Juhong WANG
IPC分类号： G06K9/00 , G06K9/46
CPC分类号： G06K9/00248 , G06K9/00281 , G06K9/00288 , G06K9/4671 , G06K9/4676
摘要： The present disclosure provides a three-dimensional facial recognition method and system. The method includes: performing pose estimation on an input binocular vision image pair by using a three-dimensional facial reference model, to obtain a pose parameter and a virtual image pair of the three-dimensional facial reference model with respect to the binocular vision image pair; reconstructing a facial depth image of the binocular vision image pair by using the virtual image pair as prior information; detecting, according to the pose parameter, a local grid scale-invariant feature descriptor corresponding to an interest point in the facial depth image; and generating a recognition result of the binocular vision image pair according to the detected local grid scale-invariant feature descriptor and training data having attached category annotations. The present disclosure can reduce computational costs and required storage space.

3. 发明申请

US20180025256A1 METHOD AND APPARATUS FOR RECOGNIZING CHARACTER STRING IN IMAGE 审中-公开
公开(公告)号：US20180025256A1
公开(公告)日：2018-01-25
申请号：US15721881
申请日：2017-09-30
申请人： Tencent Technology (Shenzhen) Company Limited
发明人： Xiang BAI , Juhong WANG , Tingting LIU , Wei CHEN , Baoguang SHI , Cong YAO , Pengyuan LV
IPC分类号： G06K9/62 , G06N3/04
CPC分类号： G06K9/6277 , G06K9/325 , G06K9/62 , G06K9/6217 , G06K2209/01 , G06N3/04 , G06N3/0454
摘要： Embodiments of this disclosure belong to the field of computer technologies and disclose a method and an apparatus for recognizing a character string in an image. The method includes: according to image data of a pre-stored sample image block including a character string, and based on a convolutional neural network algorithm, constructing an expression of a probability set corresponding to a character string recognition result of the sample image block, the expression of the probability set being constituted by a to-be-determined parameter; based on a training target of maximizing a probability that the character string recognition result determined according to the probability set is the character string included in the pre-stored sample image block, training the plurality of to-be-determined parameters to obtain a training value for each to-be-determined parameter; and when a to-be-recognized target image block is obtained, determining, based on the convolutional neural network algorithm and the training values of the plurality of to-be-determined parameters, a target probability set corresponding to the target image block, and determining, according to the target probability set, a character string recognition result of the target image block. By means of the embodiments of this disclosure, correctness of recognizing a character string can be improved.

4. 发明申请

US20160371539A1 METHOD AND SYSTEM FOR EXTRACTING CHARACTERISTIC OF THREE-DIMENSIONAL FACE IMAGE 审中-公开
标题翻译：提取三维图像特征的方法和系统
公开(公告)号：US20160371539A1
公开(公告)日：2016-12-22
申请号：US15206338
申请日：2016-07-11
申请人： Tencent Technology (Shenzhen) Company Limited
发明人： Yue MING , Jie JIANG , Tingting LIU , Juhong WANG
IPC分类号： G06K9/00 , G06T17/00 , G06K9/52 , G06T7/60 , G06T7/00 , G06K9/46
CPC分类号： G06K9/00281 , G06K9/00268 , G06K9/00302 , G06K9/4604 , G06K9/4671 , G06K9/52 , G06K2009/4666 , G06T7/11 , G06T7/13 , G06T7/60 , G06T17/00 , G06T2200/04 , G06T2207/20112 , G06T2207/30201
摘要： A method for extracting a characteristic of a three-dimensional face image includes: performing face area division, to obtain a group of face areas; projecting each face area onto a corresponding regional bounding sphere; obtaining an indication of the corresponding face area according to the regional bounding sphere, and recording the indication as a regional bounding spherical descriptor of the face area; calculating a weight of the regional bounding spherical descriptor of the face area for each face area; and obtaining a characteristic of a three-dimensional face image according to the indication of the face area and the corresponding weight.
摘要翻译：一种用于提取三维面部图像的特征的方法包括：进行面部区域划分以获得一组面部区域; 将每个面部区域投影到相应的区域边界球体上; 根据区域边界球获取对应的面部区域的指示，并将该指示记录为面部区域的区域边界球形描述符; 计算每个面部区域的面部区域的区域边界球形描述符的权重; 并根据面部区域和相应重量的指示获得三维脸部图像的特征。

5. 发明申请

US20160321541A1 INFORMATION PROCESSING METHOD AND APPARATUS 审中-公开
标题翻译：信息处理方法和装置
公开(公告)号：US20160321541A1
公开(公告)日：2016-11-03
申请号：US15108758
申请日：2015-06-11
申请人： TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED
发明人： Kang LIU , Huaijun LIU , Yanxiong LU , Juhong WANG , Tingting LIU , Liheng XU , Jun ZHAO
IPC分类号： G06N3/08 , G06N3/04
CPC分类号： G06N3/08 , G06F17/27 , G06N3/04 , G06N3/0454
摘要： An information processing method and apparatus, the method including: training a Deep Neural Network (DNN) by using an evaluation object seed, an evaluation term seed and an evaluation relationship seed (101); at a first input layer, connecting vectors corresponding to a candidate evaluation object, a candidate evaluation term and a candidate evaluation relationship to obtain a first input vector (102); at a first hidden layer, compressing the first input vector to obtain a first middle vector, and at a first output layer, decoding the first middle vector to obtain a first output vector (103); and determining a first output vector whose decoding error value is less than a decoding error value threshold, and determining a candidate evaluation object, a candidate evaluation term and a candidate evaluation relationship corresponding to the determined first output vector as first opinion information (104). By use of the technical solution, precision of extracting opinion information from an evaluation text can be enhanced.
摘要翻译：一种信息处理方法和装置，所述方法包括：通过使用评估对象种子，评估项种子和评估关系种子（101）来训练深层神经网络（DNN）; 在第一输入层处，连接与候选评估对象相对应的矢量，候选评估项和候选评估关系，以获得第一输入向量（102）; 在第一隐藏层压缩第一输入向量以获得第一中间向量，并且在第一输出层对第一中间向量进行解码以获得第一输出向量（103）; 以及确定其解码误差值小于解码误差值阈值的第一输出向量，并且确定与所确定的第一输出向量相对应的候选评估对象，候选评估项和候选评估关系作为第一意见信息（104）。通过使用技术解决方案，可以提高评估文本中提取意见信息的精度。

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