International Business Machines Corporation

University of California

Boe Technology Group Co., Ltd.

Huawei Technologies Co., Limited

Beijing Baidu Netcom Science and Technology Co., Ltd.

Samsung Electronics Co., Ltd.

Sz Dji Technology Co., Ltd.

Beijing Boe Technology Development Co., Ltd.

National Yang Ming Chiao Tung University

Beijing Baidu Netcom Science Technology Co., Ltd

Decentral Inc.

China Aviation Planning & Construction Development

Shenzhen Xing Han Laser Technology Co.ltd.

Shu Wang

Guillermo C Bazan

Brent S Gaylord

Min Fang

Nigel G Slinger

Li Fei Zheng

Wen Jie Zhu

Di Jin

Zhen Yu Shi

Bin Liu

Xin Li

Zhiguo Zhang

Zhifan Feng

Yong Zhu

Hui Rao

Xiaohong Wang

Chunguang Chai

Kristofer Alyn Duer

Babita Sharma

Xiaohan Zhang

Zhenyu Shi

Yang Zhang

Yuan Liu

Guiming Shu

Hui Zhong

Kejun Hu

John Thomas Peyton, Jr

Huawei Yu

Jason N Todd

Zhenbo Luo

Kexin Ren

Jiangzheng Wu

Xinxin Yang

Xindong Shi

David E Stewart

Ying Li

Fan Zhang

Alan J Heeger

Peng Liu

Qi Wang

Lihua Geng

Wei Zheng

Wei Deng

Ling Zhang

Xianzhen Li

Yi Ting Zhou

Jeffrey Charles Turnham

Stephen Darwin Teilhet

Ye Xu

Zhou Fang

Yingying Jiang

Chao Lu

Daniel Moses

Hu Yang

Richard Myer Goldberg

Xiong Gong

Yao Liang

Ying Wu

Guojun Zhang

Brendan Schulman

Xiangyu Zhu

Hua Xiao

Yu-Jia Chen

Shuping Gai

Hanchao Jia

Shao Feng Zhou

Chun Bao Ouyang

Mei Zhen Cao

Li Chun Wang

Wanli Chang

Tongyang Liu

Mingwei Lu

Jianlong Yuan

Ruiyi Zhu

Bart J L Steegmans

Anthony Di Iorio

Addison Taylor Cameron-Huff

Jiaqi Ge

Mansheng Zhang

Zhizhong Guan

Botao Ma

Kebo Duan

Wenshu Xiao

Rao Hui

Peiying Dong

A method for generating a pre-trained language model, includes: obtaining sample files; obtaining typography structure information and text information of the sample files by parsing the sample files; obtaining a plurality of task models of a pre-trained language model; obtaining a trained pre-trained language model by jointly training the pre-trained language model and the plurality of task models according to the typography structure information and the text information; and generating a target pre-trained language model by fine-tuning the trained pre-trained language model according to the typography structure information and the text information.

Method for generating pre-trained language model, electronic device and storage medium

A method for controlling flight of an unmanned aerial vehicle, includes receiving a data file indicating flight restriction level and range of an airport area in an airport generated according to a risk level of the airport, parsing the data file to obtain the flight restriction level and the range of the airport area, and controlling the unmanned aerial vehicle to execute a flight restriction strategy according to the flight restriction level and the range of the airport area.

Method and device for generating flight restriction zone, and method and device for controlling flight of unmanned aerial vehicle

The present disclosure discloses a movable box and a method for controlling the same, and a package storage device. The movable box includes a box body, a box door, a security lock and a verification component. The security lock is connected between the box body and the box door, the verification component is disposed on a surface of the box door and is connected to the security lock, and the verification component is configured to acquire verification information, and control the security lock to be unlocked in response to the verification information being preset information, and a first locking member is further disposed in the box body at a bottom thereof, and the first locking member protrudes downward from the bottom of the box body.

Movable box and method for controlling the same, package storage device and computer readable storage medium

This application provides a model inference method and apparatus based on a graphics rendering pipeline, and a storage medium for model inference based on a graphics rendering pipeline. The method includes: obtaining an instruction stream in a render thread; extracting and saving texture data information from the instruction stream, where the texture data information includes texture data; and inputting the texture data information to a graphics processing unit (GPU) rendering pipeline, where the GPU rendering pipeline is used to perform GPU model-based inference on the texture data based on a GPU model to obtain an inference result of the texture data, and the GPU model is a model running in a GPU. This implements model inference on the texture data, and avoids conversion of the texture data into another data type, thereby reducing I/O memory overheads.

Model inference method and apparatus based on graphics rendering pipeline, and storage medium

A graphics rendering method includes obtaining, by a central processing unit (CPU), to-be-processed vertex data. The to-be-processed vertex data is vertex data used by a graphics processing unit (GPU) for graphics rendering processing. The method also includes processing, by the CPU, the to-be-processed vertex data to obtain vertex data within a field of view of a user. The method additionally includes sending, by the CPU, the vertex data within the field of view of the user to the GPU for the graphics rendering processing.

Graphics rendering method and apparatus, and computer-readable storage medium

The present disclosure provides a method for image segmentation, an electronic device and a computer readable storage medium, relating to the field of computer vision technology and artificial intelligence technology. The method comprises: performing feature extraction on an image through a feature extraction network to obtain a feature map; performing feature map processing on the feature map to complete semantic segmentation of the image. The disclosure may effectively improve performance of semantic segmentation.

Method and apparatus for image segmentation

A method, electronic device and storage medium for generating information are disclosed. The method includes: acquiring a plurality of tag entity words from a target video, the tag entity words including a person entity word, a work entity word, a video category entity word, and a video core entity word, the video core entity word including an entity word for characterizing a content related to the target video; linking, for a tag entity word among the plurality of tag entity words, the tag entity word to a node of a preset knowledge graph; determining semantic information of the target video based on a linking result of each of the tag entity words; and structuring the semantic information of the target video based on a relationship between the node and an edge of the knowledge graph, to obtain structured semantic information of the target video.

Method, electronic device and storage medium for generating information

The present invention provides a method for determining a plane, a method for displaying Augmented Reality (AR) display information and corresponding devices. The method comprises the steps of: performing region segmentation and depth estimation on multimedia information; determining, according to the result of region segmentation and the result of depth estimation, 3D plane information of the multimedia information; and, displaying AR display information according to the 3D plane information corresponding to the multimedia information. With the method for determining a plane, the method for displaying AR display information and the corresponding devices provided by the present invention, virtual display information can be added into a 3D plane, the reality of the display effect of enhanced display can be improved, and the user experience can be improved.

Methods for determining three-dimensional (3D) plane information, methods for displaying augmented reality display information and corresponding devices

Embodiments of the disclosure disclose a method, apparatus, server, and storage medium for incorporating a structured entity, wherein the method for incorporating a structured entity can comprise: selecting a candidate entity associated with a to-be-incorporated structured entity from a knowledge graph, determining the to-be-incorporated structured entity being an associated entity based on prior attribute information of a category of the candidate entity and a preset model, merging the associated entity and the candidate entity, and incorporating the associated entity into the knowledge graph. The embodiments can select a candidate entity, and then integrate a preset model using prior knowledge, which can effectively improve the efficiency and accuracy in associating entities, and reduce the amount of calculation, to enable the structured entity to be simply and efficiently incorporated into the knowledge graph.

Method, apparatus, server, and storage medium for incorporating structured entity

A method for mining an entity focus in a text may include: performing word and phrase feature extraction on an input text; inputting an extracted word and phrase feature into a text coding network for coding, to obtain a coding sequence of the input text; processing the coding sequence of the input text using a core entity labeling network to predict a position of a core entity in the input text; extracting a subsequence corresponding to the core entity in the input text from the coding sequence of the input text, based on the position of the core entity in the input text; and predicting a position of a focus corresponding to the core entity in the input text using a focus labeling network, based on the coding sequence of the input text and the subsequence corresponding to the core entity in the input text.

Method and apparatus for mining entity focus in text

Light harvesting luminescent multichromophores that are configured upon excitation to transfer energy to, and amplify the emission from, an acceptor signaling chromophore in energy-receiving proximity therewith are provided. Also provided are compositions for labelling a target. The labelling composition may include a donor light harvesting multichromophore and an acceptor signaling chromophore in energy-receiving proximity to the donor light harvesting multichromophore. Also provided is an aqueous composition for labelling a target, including: a donor light harvesting multichromophore; an acceptor signaling chromophore in energy-receiving proximity therewith; and a sensor biomolecule. Methods for using the subject compositions are also provided.

Light harvesting multichromophore compositions and methods of using the same

An optical path test system includes a return light test unit for emitting laser light to an optical path monitoring unit to simulate return light received by the optical path monitoring unit in a normal operation; a light path monitoring unit arranged on a light path of the return light testing unit for receiving the return light and normally emitting laser light; and a power detector for receiving the laser light emitted by the light path monitoring unit so as to monitor stability of output power of the chip when the light path monitoring unit receives the return light emitted by the return light testing unit. The technical solution in the present invention emits laser light to a tested laser chip to simulate return light received by the tested laser chip in a normal operation, and a return light resistance threshold of the laser chip can be accurately evaluated.

Optical path test system and method for return light resistance of laser chip

A method and a device for determining a placement region of an item are disclosed. The method according to the present disclosure comprises: acquiring position information of an electronic identification at a bar display screen; and determining the placement region of the item according to the position information and a preset mapping relationship.

Method and device for determining placement region of item

A computer-implemented method includes obtaining, by a processor, existing security information for static application security testing (SAST). The method also includes using, by the processor, the existing security information to discover, by a machine capable of learning, new security information. The method also includes improving, by the processor, security of a computer using the new security information.

Applying machine learning techniques to discover security impacts of application programming interfaces

The disclosure provides a method for processing a video, an electronic device, and a computer storage medium. The method includes: determining a plurality of first identifiers related to a first object based on a plurality of frames including the first object in a target video; determining a plurality of attribute values associated with the plurality of first identifiers based on a knowledge base related to the first object; determining a set of frames from the plurality of frames, in which one or more attribute values associated with one or more first identifiers determined from each one of the set of frames are predetermined values; and splitting the target video into a plurality of video clips based on positions of the set of frames in the plurality of frames.

Method for processing video, electronic device, and storage medium

Growing community of inventors

Beijing, China

Shu Wang