公开(公告)号：US08472685B2

公开(公告)日：2013-06-25

申请号：US12854860

申请日：2010-08-11

Applicant: Aichi Chien ,  Bin Dong ,  Yu Mao ,  Stanley J. Osher

Inventor： Aichi Chien ,  Bin Dong ,  Yu Mao ,  Stanley J. Osher

IPC: G06K9/00

CPC classification number: G06T7/60 ,  G06K9/6207 ,  G06K2209/051 ,  G06T7/12 ,  G06T2207/10072 ,  G06T2207/10136 ,  G06T2207/20101 ,  G06T2207/20161 ,  G06T2207/30004

Abstract: A method and apparatus for volumetric image analysis and processing is described. Using the method and apparatus, it is possible to obtain geometrical information from multi-dimensional (3D or more) images. As long as an object can be reconstructed as a 3D object, regardless of the source of the images, the method and apparatus can be used to segment the target (in 3D) from the rest of the structure and to obtain the target's geometric information, such as volume and curvature.

Abstract translation: 描述了用于体积图像分析和处理的方法和装置。 使用该方法和装置，可以从多维（3D或更多）图像获得几何信息。 只要可以将对象重建为3D对象，无论图像的来源如何，该方法和装置都可用于从目标（3D）与其余结构分割目标的几何信息， 例如体积和曲率。

公开(公告)号：US12197479B2

公开(公告)日：2025-01-14

申请号：US18390496

申请日：2023-12-20

Applicant: Rui Cheng ,  Bin Dong ,  Shanshan Jiang ,  Lu Luo ,  Lei Ding

Inventor： Rui Cheng ,  Bin Dong ,  Shanshan Jiang ,  Lu Luo ,  Lei Ding

IPC: G06F16/33 ,  G06N3/045

Abstract: Disclosed are a semantic matching and retrieval method and apparatus. The semantic matching and retrieval method includes steps of obtaining both the vector representation of a query text and the vector representation of a document text; obtaining the final vector representation of the query text; obtaining the final vector representation of the document text; calculating, based on the final vector representation of the query text and the final vector representation of the document text, the similarity score between the query text and the document text; and selecting, based on the similarity scores between the query text and a plurality of document texts, a document text matching the query text from the plurality of document texts.

公开(公告)号：US20130326346A1

公开(公告)日：2013-12-05

申请号：US13588773

申请日：2012-08-17

Applicant: Zheren Zhu ,  Yongyuan Shen ,  Fu Zhao ,  Yingyu Chen ,  Bin Dong ,  Zheng Long Wei ,  Hui Wang

Inventor： Zheren Zhu ,  Yongyuan Shen ,  Fu Zhao ,  Yingyu Chen ,  Bin Dong ,  Zheng Long Wei ,  Hui Wang

IPC: G06F15/16 ,  G06F17/30 ,  G06F17/24

CPC classification number: G06Q10/101 ,  H04L67/10

Abstract: The embodiments provide a cloud brainstorming service implemented on at least one cloud server. The brainstorming service includes a message service component configured to receive a plurality of ideas, over a network, from one or more users of devices. The users represent members of a brainstorming session. The brainstorming service also includes a brainstorming logic component configured to process the plurality of ideas and store the plurality of processed ideas in an in-memory database system, and a clustering component configured to retrieve the plurality of processed ideas from the in-memory database system and arrange the plurality of processed ideas into one or more clusters, where each cluster is a group of similar ideas. The message service component is configured to provide the plurality of processed ideas that are arranged into the one or more clusters, over the network, to the one or more users for display.

Abstract translation: 这些实施例提供了在至少一个云服务器上实现的云头脑风暴服务。 头脑风暴服务包括消息服务组件，其被配置为从设备的一个或多个用户通过网络接收多个想法。 用户代表头脑风暴会议的成员。 头脑风暴服务还包括头脑风暴逻辑组件，其被配置为处理多个想法并将多个处理的想法存储在存储器内数据库系统中;以及集群组件，被配置为从存储器内数据库系统中检索多个处理的想法 并将多个处理的想法排列成一个或多个集群，其中每个集群是一组相似的观点。 消息服务组件被配置为将被布置在一个或多个集群中的多个经处理的想法通过网络提供给一个或多个用户进行显示。

公开(公告)号：US20100157066A1

公开(公告)日：2010-06-24

申请号：US12160445

申请日：2007-01-16

Applicant: Kiran Challapali ,  Bin Dong ,  Dagnachew Birru

Inventor： Kiran Challapali ,  Bin Dong ,  Dagnachew Birru

IPC: H04N17/00

CPC classification number: H04N5/08 ,  H04N5/21 ,  H04N5/4401 ,  H04N5/46 ,  H04N21/42607

Abstract: A method for detecting the presence of a television signal embedded in a received signal including the television signal and noise is disclosed. Either first-order or second order cyclostationary property of the signals may be used for their detection. When the first-order cyclostationary property is used, the following method is used, the method comprising the steps of upsampling the received signal by a factor of N, performing a synchronous averaging of a set of M segments of the upsampled received signal, performing an autocorrelation of the signal; and detecting the presence of peaks in the output of the autocorrelation function. When the second order cyclostationary property of the signal is used, the method comprising the steps of delaying the received signal by a fixed delay (symbol time), multiplying the received signal with the delayed version, looking for a tone (single frequency) in the output.

Abstract translation: 公开了一种用于检测嵌入在包括电视信号和噪声的接收信号中的电视信号的存在的方法。 信号的一阶或二阶循环平稳性可以用于它们的检测。 当使用一阶循环平稳性时，使用以下方法，该方法包括以下步骤：对接收到的信号进行上采样乘以N，对上采样的接收信号的一组M段执行同步平均， 信号的自相关; 并检测在自相关函数的输出中存在峰值。 当使用信号的二阶循环平稳性时，该方法包括以下步骤：将接收到的信号延迟固定延迟（符号时间），将接收到的信号与延迟版本相乘，在接收到的信号中寻找音调（单频） 输出。

公开(公告)号：US20070130293A1

公开(公告)日：2007-06-07

申请号：US11563857

申请日：2006-11-28

Applicant: Bin Dong ,  Xu Gu ,  Tie Li ,  Yue Ma

Inventor： Bin Dong ,  Xu Gu ,  Tie Li ,  Yue Ma

IPC: G06F15/16

CPC classification number: G06F17/30902 ,  G06F17/3089 ,  H04L67/02 ,  H04L67/1095

Abstract: The present invention provides a method and system for implementing asynchronous portal pages, comprising a portlet monitor resident on a web browser and implemented with a script. When a user interacts with a portlet, the portlet monitor sends a XMLHTTP request to the portal server. The portal server obtains the corresponding web contents from the corresponding portlet based on the request. Then, the web contents are modified and the HTTP requests therein are redirected to XMLHTTP requests. The portlet monitor uses the modified web contents to refresh the web contents of the corresponding portlet in the portal page without reloading the whole portal page. Besides, after the user submits a request for a portlet, during waiting for the portlet being refreshed, the user may continue to interact with other portlets. Thus, the present invention has the abilities of partially refreshing and asynchronous communication.

Abstract translation: 本发明提供了一种用于实现异步门户页面的方法和系统，包括驻留在web浏览器上并由脚本实现的Portlet监视器。 当用户与portlet进行交互时，portlet监视器向门户服务器发送XMLHTTP请求。 Portal服务器根据请求从相应的Portlet获取相应的Web内容。 然后，修改Web内容，并将其中的HTTP请求重定向到XMLHTTP请求。 portlet监视器使用修改的Web内容来刷新门户页面中相应Portlet的Web内容，而不重新加载整个门户页面。 此外，在用户提交对portlet的请求之后，在等待刷新的Portlet期间，用户可以继续与其他portlet进行交互。 因此，本发明具有部分刷新和异步通信的能力。

公开(公告)号：US12175206B2

公开(公告)日：2024-12-24

申请号：US17821227

申请日：2022-08-22

Applicant: Tianxiong Xiao ,  Rui Cheng ,  Bin Dong ,  Shanshan Jiang ,  Jiashi Zhang

Inventor： Tianxiong Xiao ,  Rui Cheng ,  Bin Dong ,  Shanshan Jiang ,  Jiashi Zhang

IPC: G06F40/30 ,  G06F16/33 ,  G06F16/332 ,  G06F40/205 ,  G06F40/40 ,  G06F40/47 ,  G06F40/56 ,  G06N3/0455 ,  G06N5/02 ,  G06N7/00

Abstract: A method and an apparatus for machine reading comprehension, and a non-transitory computer-readable recording medium are provided. In the method, a paragraph-question pair is obtained, and subword vectors corresponding to subwords in the paragraph-question pair are generated. Then, for each subword, relative positions of the subword with respect to the other subwords are determined based on distances, and self-attention information of the subword in a first part and mutual attention information of the subword in a second part are calculated by using the relative positions and the subword vector. Then, a fusion vector of the subword is generated based on the self-attention information and the mutual attention information. Then, the fusion vectors of the subwords are input to a decoder of a machine reading comprehension model so as to obtain an answer predicted by the decoder.

公开(公告)号：US11562123B2

公开(公告)日：2023-01-24

申请号：US17215068

申请日：2021-03-29

Applicant: Yixuan Tong ,  Yongwei Zhang ,  Bin Dong ,  Shanshan Jiang ,  Jiashi Zhang

Inventor： Yixuan Tong ,  Yongwei Zhang ,  Bin Dong ,  Shanshan Jiang ,  Jiashi Zhang

IPC: G06F40/166 ,  G06K9/62 ,  G06N3/08

Abstract: A method and an apparatus for fusing position information, and a non-transitory computer-readable recording medium are provided. In the method, words of an input sentence are segmented to obtain a first sequence of words in the input sentence, and absolute position information of the words in the first sequence is generated. Then, subwords of the words in the first sequence are segmented to obtain a second sequence including subwords, and position information of the subwords in the second sequence are generated, based on the absolute position information of the words in the first sequence, to which the respective subwords belong. Then, the position information of the subwords in the second sequence are fused into a self-attention model to perform model training or model prediction.

公开(公告)号：US20220164536A1

公开(公告)日：2022-05-26

申请号：US17455967

申请日：2021-11-22

Applicant: Yixuan TONG ,  Yongwei ZHANG ,  Bin DONG ,  Shanshan JIANG ,  Jiashi ZHANG

Inventor： Yixuan TONG ,  Yongwei ZHANG ,  Bin DONG ,  Shanshan JIANG ,  Jiashi ZHANG

IPC: G06F40/295

Abstract: A method and an apparatus for sequence labeling on an entity text, and a non-transitory computer-readable recording medium are provided. In the method, a start position of an entity text within a target text is determined. Then, a first matrix is generated based on the start position of the entity text. Elements in the first matrix indicates focusable weights of each word with respect to other words in the target text. Then, a named entity recognition model is generated using the first matrix. The named entity recognition model is obtained by training using first training data, the first training data includes word embeddings corresponding to respective texts in a training text set, and the texts are texts whose entity label has been labeled. Then, the target text is input to the named entity recognition model, and probability distribution of the entity label is output.

公开(公告)号：US11270212B2

公开(公告)日：2022-03-08

申请号：US15919355

申请日：2018-03-13

Applicant: Lei Ding ,  Yixuan Tong ,  Bin Dong ,  Shanshan Jiang ,  Yongwei Zhang

Inventor： Lei Ding ,  Yixuan Tong ,  Bin Dong ,  Shanshan Jiang ,  Yongwei Zhang

IPC: G06N5/02 ,  G06N3/04 ,  G06N3/08 ,  G06F16/28 ,  G06F16/31 ,  G06F16/951 ,  G06F16/22 ,  G06F16/901 ,  G06F40/279 ,  G06F40/295

Abstract: Knowledge graph processing method and device are disclosed. The method includes steps of obtaining an entity set containing a first entity, a second entity, and relation information; acquiring text information and image information related to the first entity and the second entity; generating a first structural information vector of the first entity and a second structural information vector of the second entity, and creating a first text information vector of the first entity, a first image information vector of the first entity, a second text information vector of the second entity, and a second image information vector of the second entity; and building a joint loss function so as to attain a first target vector of the first entity, a second target vector of the second entity, and a target relation vector of the relation information between the first entity and the second entity.

公开(公告)号：US20210390454A1

公开(公告)日：2021-12-16

申请号：US17343955

申请日：2021-06-10

Applicant: Tianxiong XIAO ,  Yixuan TONG ,  Bin DONG ,  Shanshan JIANG ,  Jiashi ZHANG

Inventor： Tianxiong XIAO ,  Yixuan TONG ,  Bin DONG ,  Shanshan JIANG ,  Jiashi ZHANG

IPC: G06N20/00 ,  G06F40/20 ,  G06K9/62

Abstract: Disclosed is an apparatus for training a machine reading comprehension model. The apparatus is inclusive of a distance calculation part configured to calculate, based on a position of each word within a training text and a position of an answer label within the training text, a distance between the same word and the answer label; a label smoothing part configured to input the distance between the same word and the answer label into a smooth function to obtain a probability value corresponding to the same word, outputted from the smooth function; and a model training part configured to make the probability value corresponding to the same word serve as a smoothed label of the same word so as to train the machine reading comprehension model.