Huawei Technologies Co., Limited

Zte Corporation

Tencent Technology (shenzhen) Company Limited

Dongguan Sunland Technology Co., Ltd.

Other

Honor Device Co., Ltd.

Nanjing University

Peking University

Innocom Technology(shenzhen) Co., Ltd.

Innolux Display Corporation

Nanjing University Yancheng Environmental Protection Technology and Engineering Research Institute

Lifepro Fitness LLC

Xi'an Laser Tech Medical Technology Co., Ltd.

Bell Holdings (shenzhen) Technology Co., Ltd

Shenzhen Neocura Biotechnology Corporation

Yi Tong Wang

Liqing Zhang

Jiayin Zhang

Qiao Sun

Silei Huyan

Dong Lin

Shiqiang Lu

Jianglei Ma

Yan Chen

Wei Zhu

Yu Cao

Yiqun Wu

Yong Huang

Xing Ji

Zuobing Wang

Lijian Mei

Shenghui Huang

Xin Tao

Jun Ni

Bao Lu

Hongbo Qi

Jinfu Zhou

Xiao Long Zhu

Zhiyong Sun

Lei Zhang

Yongxia Lyu

Kun Li

Wei Dong Chen

Xin Yang

Xiaoyan Bi

Liang Xia

Tao Li

Hanyang Wang

Chao Wang

Jian Wang

Egon Schulz

Xin Lu

Yun Zhang

Zhe Zhang

Bo Xu

Jie Dong

Gong Zhang

Chan Zhou

Yingtao Li

Wei Jiang

Hui Yu

Shengdong Zhang

Zheng Zhou

Jia Ya Jia

Yongming Liang

Malte Schellmann

Lei Huang

Chen Chen

Jiaya Jia

Xiaoyong Shen

Qi Zhang

Tao Ma

Yuwing Tai

Jie Fan

Yuqing Zhao

Min Luo

Jingmin Luo

Zhi Chen

Xipeng Li

Yuan Fang

Zhaoyang Li

Linzhang Wang

Xuandong Li

Sheng Zan

Xin He

Jinnan Wang

Tian Zhang

Hao Meng

Zuofeng Zhang

Qi Song

Dongfang Ning

Ziwen Chen

Zhiguang Dai

Yan-Kai Zhang

Jiani Zhang

Cheng Cheng

Lianqiao Sun

Dedong Han

Song Dang

De Yang

Jun-Hua Yang

Jiabin Liang

Kai Ning Huang

Xiaoqu Zhang

Yiming Shen

Meiyan Liao

Chuan Lv

Yibo Chen

Ruqi Han

Ren Jian Chen

Youdong Pan

Ji Wan

This application provides a tuning component, including: a plurality of pins, where the plurality of pins include a first pin, a second pin, a third pin, and a fourth pin; a reactance element, where the reactance element is connected between the first pin and the second pin; a switch assembly, disposed between the third pin and the fourth pin; a first internal branch, where one end of the first internal branch is connected to the third pin; and a second internal branch, where one end of the second internal branch is connected to the fourth pin, where the other end of the first internal branch is connected to the other end of the second internal branch to form an integrated end, and the integrated end is connected to the first pin. This application further provides an antenna apparatus and a terminal device, to help reduce headroom requirement of antenna.

Tuning component, antenna apparatus, and terminal device

A method and apparatus to configure grant-free transmission resources are provided. At least two configuration options can co-exist for configuring the grant-free transmission resources. The base station may explicitly or implicitly notify a user equipment which option is selected for grant-free transmission by that user equipment.

Methods and systems for resource configuration of wireless communication systems

Provided are a Time-Interleaved Successive Approximation Register Analog-to-Digital Converter, TISAR ADC, and a calibration method thereof. The calibration method for the TISAR ADC may include: sampling an analog signal input into the TISAR ADC to generate a reference digital signal (S); according to the reference digital signal and output digital signals generated by analog-to-digital conversion sub-modules of the TISAR ADC, obtaining capacitor array calibration parameters and time delay calibration parameters of the analog-to-digital conversion sub-modules; adjusting capacitor arrays of the corresponding analog-to-digital conversion sub-modules according to the capacitor array calibration parameters, respectively; and adjusting time delays of the corresponding analog-to-digital conversion sub-modules according to the time delay calibration parameters, respectively.

Time-interleaved successive approximation analog to digital converter and calibration method thereof

A method for generating a special effect for social networking interaction in a virtual environment of a game is performed by an electronic device. The method includes: displaying an object presentation interface of a target battle of the game when loading a virtual scene corresponding to the target battle, the object presentation interface being used for displaying a plurality of virtual objects participating in the target battle; receiving a special effect generating instruction for a first virtual object of the plurality of virtual objects, the special effect generating instruction being used for instructing to generate a special effect based on the first virtual object, and the first virtual object corresponding to a user of the electronic device triggering the special effect; and generating the special effect identifying the first virtual object in the object presentation interface.

Method and apparatus for generating special effect in virtual environment, device, and storage medium

Embodiments of this application provide a neural network model deployment method, a prediction method and a device. The described features can implement deployment of a neural network model to improve the universality of the deployment of the neural network model to the terminal device by obtaining a layer definition and an operation parameter of each network layer of an initial neural network model, executing a target network layer corresponding to the network layers, applying relational connections amongst the target network layers using a net class, converting the operation parameters into a preset format, obtaining a target operation parameter based on the preset format, loading a corresponding target operation parameter in the target network layer, and obtaining a target neural network model based on the target operation parameter.

Neural network model deployment method, prediction method and related device

This application discloses an image processing method, device, and apparatus, and a storage medium. The method is performed by a computing device, the method including: receiving an input image; determining a context feature of the input image; determining a first feature set and a second feature set according to the context feature and based on a size of a target image and a location of the input image in the target image; adjusting the second feature set according to a first feature statistic of the first feature set, to obtain an adjusted second feature set; and generating the target image based on the adjusted second feature set and the first feature set.

Image processing method and apparatus, device, and storage medium

A method and a system for calculating tumor neoantigen burden (TNB) are provided. The method includes: step S: processing a normal sample and a tumor sample, sequencing a specific region and detecting somatic mutations in the sample; step S: annotating and filtering the somatic mutations, and translating to obtain mutant peptide sequences of a patient; step S: filtering the mutant peptide sequences to obtain neopeptide sequences based on a proteome of the normal sample; step S, performing a human leukocyte antigen (HLA) typing analysis based on alignment data of the normal sample to obtain HLA genotypes of the sample; step S, predicting binding affinities between the neopeptide sequences and the HLA genotypes to obtain specific neoantigens of the sample, and performing a weighted scoring on each of the specific neoantigens and calculating the TNB of the sample.

Method and system for calculating tumor neoantigen burden

Disclosed are a flexible screen terminal device and a display method therefor, and a non-transitory computer-readable storage medium. The display method may include: determining a folding boundary line corresponding to a folding operation in response to a detection of the folding operation corresponding to the flexible screen terminal; and performing a split-screen display operation based on the folding boundary line and a preset display rule of the flexible screen terminal device.

Flexible screen terminal and display method therefor, and computer-readable storage medium

Embodiments of the disclosure disclose a method, an apparatus, a computer device, and a storage medium for inpainting an image. In an embodiment, an image inpainting method includes: determining, from a target image, a first region to be inpainted and a second region that is not to be inpainted; performing feature extraction on the second region based on different receptive fields and spatial resolutions, to obtain feature information of a plurality of scales; generating a texture of the first region based on the feature information of the plurality of scales; and filling the first region in the target image with the generated texture, to obtain an inpainted image.

Image inpainting method and apparatus, computer device, and storage medium

A face key point detection method includes determining, according to an image containing a face, a multi-channel feature map of the image; converting the multi-channel feature map into a predetermined channel quantity of target feature maps; performing a convolution operation on each target feature map in the predetermined channel quantity of target feature maps by using a convolution kernel corresponding to each target feature map; generating a feature vector corresponding to the image based on a result of the convolution operation on each target feature map; and determining key point coordinates of the face on the image according to the feature vector.

Face key point detection method and apparatus, storage medium, and electronic device

A video editing method, apparatus and storage medium are provided. The method includes obtaining an object, the object including one or more images; determining a content element of the object for video editing, the content element having a content type identifier; determining a material set identifier corresponding to the content type identifier according to a first behavior tree logic; determining a video editing material set corresponding to the material set identifier; and obtaining an edited video according to the content element and the video editing material set.

Video editing method, apparatus, and device, and storage medium

Massager

This application discloses a network slicing method. The method includes obtaining metadata information of each of multiple traffic flows, determining a classification policy according to metadata information of the multiple traffic flows, determining a network slicing policy according to the classification policy, and the network slicing policy includes a mapping relationship between a traffic flow type and a network slice and a slice weight of the network slice, and determining a resource node policy according to the network slicing policy, where the resource node policy includes a mapping relationship between at least one resource node in the network and the at least one network slice and a resource weight of each resource node, and the resource weight of the resource node indicates a ratio of a resource of each of network slices corresponding to the resource node to a resource of the resource node.

Network slicing method and system

A laser therapeutic apparatus includes a laser and a therapeutic optical fiber. The therapeutic optical fiber is configured for being implanted into a body of a patient during surgery to perform a repair treatment on a spinal cord site to-be-treated by irradiation and then being removed from the body of the patient after the surgery. The therapeutic optical fiber includes N number of laser fibers, N&#x2212;1 number of optical fiber connection components, an optical fiber guiding structure, and an optical fiber controller; the N number of laser fibers are coupled with one another by the N&#x2212;1 number of optical fiber connection components to form a cascaded optical fiber structure, an end of the cascaded optical fiber structure is coupled to the optical fiber guiding structure, and another end of the cascaded optical fiber structure is coupled to the optical fiber controller.

Laser therapeutic apparatus and spinal cord repairing method

Growing community of inventors

Shenzhen, China

Yi Tong Wang