Qualcomm Incorporated

Boe Technology Group Co., Ltd.

International Business Machines Corporation

Chengdu Boe Optoelectronics Technology Co., Ltd.

Apple Inc.

Tsinghua University

Intel Corporation

Huawei Technologies Co., Limited

Chinese Academy of Sciences

Other

General Electric Company

Beijing Xiaomi Mobile Software Co., Ltd.

Globalfoundries Inc.

Xilinx, Inc.

Alibaba Group Holding Limited

Yu Zhang

Wanshi Chen

Chao Wei

Chenxi Hao

Liangming Wu

Peter S Gaal

Qiaoyu Li

Lan Tang

Junxin Duan

Alexandros Manolakos

Ye Liu

Hao Xu

Shixin Geng

Bochang Wang

Joseph Binamira Soriaga

Tingfang Ji

Guangyun Tong

Min Huang

Tan Jiang

Wei Zeng

Haitong Sun

Huiyan Li

Kun Wang

Liang Wang

Lin Luo

Xuefei Qin

Zhuolong Li

Dawei Zhang

Yuchul Kim

Pavan Kumar Vitthaladevuni

Jilei Hou

Li Yi

Wei Zhang

Yuwei Ren

Shun Xiang Yang

Ling Lan

Yi Huang

Wei Zhao

Bo Chen

Miao Liu

Hao Zhou

Yong Yao

Tao Luo

Peng Cheng

June Namgoong

Xu Chen

Ruifeng Ma

Weihao Hu

Randall Kramer

Songling Huang

Shen Wang

Bernardo Vidal, Jr

Jianan Hao

Yi Cao

Juan Montojo

Jing Jiang

Haipeng Lei

Peng Ji

Ming Lei

Zhanchang Bu

Gang Huang

Randall Scott Deinhammer

Guanfan Mao

Changgui Wang

Shu Chao Wan

Guokui Wang

Tengfei Wang

Yongji Xie

Wen Chai

Weiyun Huang

Fan Yang

Yang Li

Neng Wang

Xiuyun Chen

Fan Wang

Vugranam Chakravarthy Sreedhar

Brett McBrayer

Chi Yu

Xinyu Shen

Yan Cui

Lili Jia

Michael John Akerman

Zhi Feng

Guangwu Chen

Christian Isak Jorgensen

Chuan Peng

James Lavigne

Lulu Wang

Da Hu Kuang

Thomas Patrick Gibbons

Lijin Zhao

Fuxue Liang

Junjun Yang

Hu Gu

Xuan Yang

Ying Dai

Guanying Liu

Shiyu Lin

Guihua Lu

A resource adjustment method includes determining a resource adjustment quantity when creating a first virtual port or deleting a second virtual port on a server, where the resource adjustment quantity is a to-be-adjusted value of a resource occupied by a virtual switch (vSwitch) on the server, where the first virtual port is a to-be-created virtual port between the vSwitch and a first virtual machine, and where the second virtual port is a to-be-deleted virtual port between the vSwitch and a second virtual machine on the server.

Resource adjustment method and apparatus

Disclosed are a backlight module, a display module and a display apparatus. The backlight module includes: a back plate including a bottom plate and a plurality of side plates around the bottom plate, where the plurality of side plates and the bottom plate enclose an assembly space; a light guide plate in the assembly space, including a plurality of side faces each disposed opposite to one of the side plates, where a first gap is provided between each side face and the opposite side plate; at least two light bars in different first gaps, where an emission side of each light bar is disposed opposite to the side face of the light guide plate, the first gap with a light bar is a first sub-gap, and a plurality of elastic members, at least part of which are positioned in respective first sub-gaps.

Backlight module, display module and display apparatus

Techniques related to poly-scale kernel-wise convolutional neural network layers are discussed. A poly-scale kernel-wise convolutional neural network layer is applied to an input volume to generate an output volume and include filters each having a number of filter kernels with the same sample rate and differing dilation rates optionally in a repeating pattern of dilation rate groups within each of filters with the pattern of dilation rate groups offset between the filters the poly-scale kernel-wise convolutional neural network layer.

Poly-scale kernel-wise convolution for high-performance visual recognition applications

Embodiments of the present invention provide a control method for an image acquisition device, a control device therefor, and a storage medium, relate to the field of the image acquisition device, and aim to realize synchronization of an operation timing signal of the image acquisition device and an external trigger signal. The method comprises: receiving image data acquired by the image acquisition device; analyzing the image data, obtaining an image timing according to an analysis result, and determining a frame synchronization signal of the image data output by the image acquisition device according to the image timing; determining a phase offset between the frame synchronization signal and a preset trigger signal; and adjusting a phase of a control signal based on the phase offset, wherein the control signal is configured for adjusting an operation timing of the image acquisition device.

Phase and exposure synchronization control of image acquisition devices

Embodiments of the present disclosure relate to a method for task scheduling and an electronic device. The method comprises: based on determining there is a task to be scheduled in an online task set of a waiting queue, an electronic device schedules the task based on a preset online scheduling mode which may be a sequential mode, a throughput mode, or a round-robin mode. Accordingly, at least one processing engine of the electronic device can process the task.

Task scheduling based on scheduling mode

A connection method for a wireless smart wearable device is performed by a terminal device, and includes: receiving a connection switching instruction of the wireless smart wearable device from a preset control interface of the terminal device; determining a target device according to the connection switching instruction; and instructing, according to a preset parameter of the wireless smart wearable device, the target device to be connected with the wireless smart wearable device according to the preset parameter.

Connection method and apparatus for wireless smart wearable device and storage medium

The present disclosure provides a display module and a display apparatus. The display module includes a display panel, a backlight assembly, an intermediate frame and a backplane; the backplane includes a backplane body on a side of the backlight assembly away from the display panel; the backplane body includes a contact structure recessed in a direction from a side away from the light guide assembly toward a side close to the light guide assembly. The contact structure is in contact with the light guide assembly; a receiving space is between the backplane body and the light guide assembly and on a side of the contact structure close to a lateral backlight source; an elastic contact member is in a receiving space and is in contact with the backplane body and is adjacent to the light guide assembly; the intermediate frame includes an intermediate frame body surrounding the backlight assembly.

Display module and display apparatus

A system includes a high bandwidth memory (HBM) and a convolutional neural network (CNN) engine. The HBM includes a virtual bank portion and a system memory portion. The virtual bank portion is configured to store a feature map data and the system memory portion is configured to support data exchanges with a host. The CNN engine includes a convolutional unit configured to execute convolutional layer instructions, a depthwise convolutional unit configured to execute depthwise layer instructions, and a first on-chip buffer. The first on-chip buffer is configured to receive and store the feature map data from the virtual bank portion or receive and store data results from the convolutional unit. The first on-chip buffer is further configured to send the feature map data or the data results from the convolutional unit to the depthwise convolutional unit for processing.

Neural network architecture with high bandwidth memory (HBM)

A method of wireless communication by a user equipment (UE), comprises inputting sensor data, captured at the UE, to a local machine learning model. The method also includes extracting features from the sensor data, with the local machine learning model, while anonymizing the sensor data. The method further includes transmitting the features to a base station, and receiving a handover decision from the base station based on the features. A method of wireless communication by abase station inputs anonymized sensor feature data, received from a user equipment (UE), into a network machine learning model. The base station also inputs handover decision information into the network machine learning model. The method further includes inferring a handover decision based on the handover decision information and the anonymized sensor feature data, and transmitting the handover decision to the UE.

Machine learning handover prediction based on sensor data from wireless device

Embodiments of the present disclosure relate to methods and apparatuses for determining a HARQ-ACK codebook for multi-slot PDSCH transmission. According to some embodiments of the disclosure, a method for wireless communications performed by a UE may include: receiving a first plurality of downlink control information (DCI) formats for scheduling a second plurality of physical downlink shared channel (PDSCH) transmissions on at least one serving cell of the UE; receiving the second plurality of PDSCH transmissions based on the first plurality of DCI formats; generating a HARQ-ACK codebook based on the indicators in the first plurality of DCI formats; and transmitting the HARQ-ACK codebook.

Method and apparatus for determining hybrid automatic repeat request acknowledgement (HARQ-ACK) codebook for multi-slot physical downlink shared channel (PDSCH) transmission

The present application relates to a method and an apparatus for multiple uplink transmissions. The method includes: receiving a first control information for a first uplink transmission; receiving a second control information for a second uplink transmission; and determining a beam for transmitting the first uplink transmission, wherein the beam is indicated in the first control information or indicated in the second control information.

Method and apparatus for multiple uplink transmissions

The disclosure relates to a method, apparatus, computer-readable medium and electronic device for program loading. The method includes: loading the bin file at a program loading speed that is a first speed, adjusting the program loading speed to a second speed based on the configuration parameter in the bin file, the second speed being faster than the first speed, and then loading a FSBL at the program loading speed that is the second speed. By executing the configuration parameter in the bin file to adjust the speed of the Bootrom loading the FSBL from flash memory, the time for the Bootrom to load FSBL is shortened, and thus embedded systems are enabled to be compatible with various flash memories while also being applicable in occasions sensitive to startup time.

Method, apparatus and computer-readable medium for program loading

Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment may determine an automatic gain control parameter, for a group of downlink symbols associated with a base station, based at least in part on an automatic gain control resource included in the group of downlink symbols. The user equipment may perform, based at least in part on the automatic gain control parameter, automatic gain control for one or more data symbols included in the group of downlink symbols. Numerous other aspects are provided.

Receiver automatic gain control

Methods, systems, and devices for wireless communications are described. In some examples, a UE may receive an indication of a set of sounding reference signal (SRS) parameters corresponding to a set of SRS resources for transmitting SRSs, where the set of SRS resources may refer to frequency, or time, or both. In some examples, the SRS parameters may include, among other examples, a frequency allocation, a frequency overlap parameter, a number of allocated symbols, a comb value, a cyclic shift, a comb offset, a frequency hopping parameter, a repetition parameter, a symbol grouping parameter, or any combination thereof. The UE may determine an SRS configuration for the one or more SRSs based on the set of SRS parameters and transmit the one or more SRSs based on the configuration. In some examples, the SRS configuration includes a configuration for SRS frequency hopping, or SRS repetition, or both.

Enhanced sounding reference signal resource configurations

Provided is a support bracket for supporting a diffuser, including: a support post and a mounting part arranged in a first direction. The mounting part includes: an elastic connection part and a base arranged opposite to each other along the first direction, the elastic connection part is connected to the base, the support post extends in the first direction and an end of the support post close to the mounting part is fixed to the elastic connection part, and the elastic connection part is configured to be elastically deformable in the first direction to change a distance between the end of the support post close to the mounting part and the base in the first direction. Further provided are a sub-backlight module, a display device and a splicing display module.

Support bracket, sub-backlight module, display device and splicing display module

Growing community of inventors

Beijing, China

Yu Zhang