Shenzhen University

Shenzhen China Star Optoelectronics Technology Co., Ltd.

Chinese Academy of Sciences

Gree Electric Appliances, Inc. of Zhuhai

Huawei Technologies Co., Limited

Gree Green Refrigeration Technology Center Co., Ltd. of Zhuhai

Ocean's King Lighting Science and Technology Co., Ltd.

Green Refrigeration Equipment Engineering Research Center of Zhuhai Gree Co., Ltd.

Tcl China Star Optoelectronics Technology Co., Ltd.

Tencent Technology (shenzhen) Company Limited

Shenzhen Goodix Technology Co., Ltd.

Tianma Micro-electronics Co., Ltd.

Shenzhen Institutes of Advanced Technology

Gree Electric Appliances (wuhan) Co., Ltd

Shenzhen Ocean's King Lighting Engineering Co., Ltd.

Hui Huang

Yusheng Hu

Yong Xiao

Ruizhen Hu

Mingjie Zhou

Ping Wang

Jia Xu

Liping Ren

Huijun Wei

Bin Chen

Hui Li

Ouxiang Yang

Daniel Cohen-Or

Jian Wu

Jian Wang

Zhongcheng Du

Shebing Liang

Suhua Lu

Yang Zhou

Jing Liu

Quanzhong Gao

Pengkai Wan

Sen Yang

Chaoyi Yan

Wei Sun

Peng Wang

Hao Zhang

Xinyu Wang

Tong Tong

Fayou Luo

Peng Hu

Lei Niu

Fang Zhang

Bin Wang

Xiaobo Zhang

Bo Zheng

Jinfei Shi

Xiaoping Sun

Ping Huang

Hui Zhang

Dechao Song

Peilin Yang

Weilin Guo

Jianning Liu

Heng Xu

Dongsuo Chen

Wenming Zhang

Xueying Zeng

Kangxue Yin

Huajie Chen

Minglun Gong

Xiaoming Feng

Huifang Luo

Shihao Wu

Fei Wu

Zhenhua Zhang

Qian Zheng

Lingchao Kong

Baoquan Chen

Ke Xie

Hongwei Zhu

Jixing Chen

Rongting Zhang

Ying Jiang

Daofu Hu

Shaolin Chen

Yanjun Hu

Peizhen Que

Yuanbin Zhai

Shu Pang

Zhidong Zhang

Tangtang Gu

Yilin Liu

Di Lin

Liu Xiang

Jia Xie

Liying Deng

Sichen Wang

Chong Chen

Sheng Chen

Jianrui Yang

Jianping Huang

Guochen Liu

Chuanshun Huang

Xiangfei Liang

Xiaohui Zhou

Yiming Liang

Shunqing Liu

Jingwen Wang

Jinquan Zhang

Zhong Cui

Yan Li

Xiaochun Cai

Xin Chang

Tao Tian

Man Wu

Haiqiang Huang

Gang Yao

Qianglian Lin

A method for generating a strategy of an object transport-and-pack process, and a computer device. The method includes: obtaining a priority diagram of a to-be-packed object set in an initial container; encoding the priority diagram; performing a convolution calculation by a neural network, and determining a current to-be-packed object; generating a packing sequence of to-be-packed objects in the to-be-packed object set; and determining a strategy of a packing process of the to-be-packed object set according to a packing target, the packing sequence of the to-be-packed objects, and a transport state of each to-be-packed object and a preset layout strategy.

Method and apparatus for generating strategy of object transport-and-pack process, and computer device

A method, an apparatus for continuous path planning, a computer device, and a storage medium. The method designs the optimization function based on the rapidly exploring random tree to plan path, and the optimal path is screened out from the random tree according to target function including the reconstruction completeness optimization function, the path effectiveness optimization function, and the path smoothness optimization function when the reconstruction degree of the preset sampling points is determined to meet the preset requirement.

Method and apparatus for continuous path planning, computer device, and storage medium

A floor plan image generating methodology is provided. The methodology includes: acquiring a boundary of a target building and a layout constraint of the target building; outputting multiple first floor plan images according to the layout constraint of the target building; selecting multiple second floor plan images from the multiple first floor plan images; applying a layout constraint of each of the second floor plan images to the boundary of the target building, and obtaining a layout of the target building corresponding to each of the multiple second floor plan images; inputting the layout of the target building and the boundary of the target building into a floor plan image generating network; and obtaining a predicted floor plan image of the target building outputted by the floor plan image generating network.

Floor plan image generating method and device, computer device and storage medium

A method for generating a robot exploration path for a robot to move along includes: establishing a point cloud scene according to single-frame point cloud data collected by the robot, the point cloud scene includes a plurality of data points; classifying and marking each of the data points, the classification mark includes a ground point and an obstacle point, and taking the data points marked as ground points as a ground point cloud; generating a confidence map according to the ground point cloud, the confidence map is configured to display a location and a confidence of each of the ground points in the ground point cloud; generating a plurality of access nodes according to the confidence map; and generating an exploration path according to the access nodes.

Method for generating robot exploration path for a robot to move along, computer device, and storage medium

An object attribute inference method, a storage medium and an electronic device. The method includes the following steps: training a preset neural network by using a training sample comprising an action sequence and a target object attribute tag; where the action sequence is an interactive action sequence of a human body and an object. In this way, the object attribute inference model obtained through training can recognize the object attributes from the interaction action of the human body and the object, the object attributes include and are not limited to the weight, the shape, the hardness degree and the like of the object, and therefore the inference module obtained through training has the advantages of being universal in object attribute inference and wide in application range.

Object attribute inference method, storage medium and electronic device

The present disclosure provides a three-dimensional element layout visualization method and apparatus. The three-dimensional element layout visualization method includes: determining a bounding box of each three-dimensional element in a visualization interface; projecting the bounding box of each three-dimensional element in a target projection direction to obtain edge elements of the bounding box of each three-dimensional element in the visualization interface; and determining, according to positions of the edge elements in the visualization interface, at least one edge element set satisfying a first preset condition, and displaying a collinearity identification corresponding to the edge element set in the visualization interface.

Three-dimensional element layout visualization method and apparatus

A point cloud data processing method and device, a computer device and a storage medium are provided. The method includes: acquiring point cloud data, and constructing a corresponding neighboring point set for each of data points in the point cloud data; calculating Hausdorff distances between the neighboring point set and a pre-constructed kernel point cloud to obtain a distance matrix; calculating a convolution of the neighboring point set with the distance matrix and a network weight matrix in a Hausdorff convolution layer in an encoder, to obtain high-dimensional point cloud features, the encoder and a decoder being two parts in a deep learning network; and reducing feature dimension of the high-dimensional point cloud features through the decoder, so that a classifier performs semantic classification on the point cloud data according to object point cloud features obtained by the dimension reduction.

Point cloud data processing method and device, computer device, and storage medium

A rotor structure, a permanent magnet auxiliary synchronous reluctance motor and an electric vehicle. The rotor structure includes a rotor body, and permanent magnet slot groups are disposed on the rotor body; the permanent magnet slot groups each include an outer layer permanent magnet slot; and a third bent slot and a fourth bent slot are further disposed on the rotor body. A third angle is formed by a length directional geometric center line of the third bent slot and a length directional geometric center line of a first segment of the outer layer permanent magnet slot a fourth angle is formed between a length directional geometric center line of the fourth bent slot and a length directional geometric center line of a second segment of the outer layer permanent magnet slot.

Rotor structure, permanent magnet auxiliary synchronous reluctance motor, and electric vehicle

The present disclosure provides a compressor and an air conditioner having the same. The compressor includes: a main shaft with a convex portion and a slip sheet; a cylinder; and an air inlet and outlet device including a disk body and an air suction port including an outer side, an inner side and a connecting side located between the outer side and the inner side, wherein the outer side is overlapped with an inner wall of the cylinder or is located on the inner side of the inner wall of the cylinder, the inner side is overlapped with an outer wall of the convex portion or is located on the outer side of the convex portion, and the connecting side is overlapped with a side wall of the slip sheet or is located on the inner side of the side wall of the slip sheet.

Air conditioner having compressor including curved suction port and a plurality of exhaust ports

A display device and a manufacturing method of the display device are provided. The display device includes a substrate; a pixel definition layer disposed on the substrate and having a plurality of pixel openings; a surface-active nanolayer disposed on a surface of the substrate and on a surface extending to the pixel definition layer, wherein the surface-active nanolayer covers a plurality of nanoparticles; and a light-emitting layer disposed in the plurality of pixel openings.

Display device and manufacturing method of display device

Disclosed are a mesh reconstruction method and apparatus for a transparent object, a computer device and a storage medium. The method includes: acquiring object images of the transparent object at multiple capture view angles and calibration information corresponding to an image capture device, the image capture device configured to capture being the object images; generating an initial mesh model corresponding to the transparent object according to the object images acquired at the multiple capture view angles; determining a light ray refraction loss corresponding to an emergent light ray of the image capture device according to the calibration information, and determining a model loss corresponding to the initial mesh model according to the light ray refraction loss; and reconstructing the initial mesh model according to the model loss, to obtain a target mesh model corresponding to the transparent object.

Mesh reconstruction method and apparatus for transparent object, computer device and storage medium

The present application relates to methods and apparatuses for three-dimensional reconstruction of a transparent object, computer devices, and storage mediums. The method includes acquiring silhouettes and light correspondences of a to-be-reconstructed transparent object under different viewing directions, acquiring an initial rough transparent object model of the to-be-reconstructed transparent object, and filtering out light rays involved in multiple refractions and total reflections by backward ray tracing; acquiring surface normal vectors and Snell normal vectors of the initial rough transparent object model in camera device views, and performing a first optimization on the initial rough transparent object model by constraining consistency between the surface normal vectors and the Snell normal vectors of the initial rough transparent object model in the camera device views, and acquiring a point cloud reconstruction model; acquiring Poisson sample points of the initial rough transparent object model, and updating the point cloud reconstruction model according to the Poisson sample points.

Methods for three-dimensional reconstruction of transparent object, computer devices and storage mediums

The present disclosure relates to a point cloud feature enhancement and apparatus, a computer device and a storage medium. The method includes: acquiring a three-dimensional point cloud, the three-dimensional point cloud including a plurality of input points; performing feature aggregation on neighborhood point features of the input point to obtain a first feature of the input point; mapping the first feature to an attention point corresponding to the corresponding input point; performing feature aggregation on neighborhood point features of the attention point to obtain a second feature of the corresponding input point; and performing feature fusion on the first feature and the second feature of the input point to obtain a corresponding enhanced feature. An enhancement effect of point cloud features can be improved with the method.

Point cloud feature enhancement and apparatus, computer device and storage medium

A rotor structure, a permanent magnet auxiliary synchronous reluctance motor and an electric vehicle, the rotor structure includes a rotor body and an outer layer permanent magnet. The rotor body is provided with a magnetic steel slot group. The magnetic steel slot group includes an outer layer magnetic steel slot. The outer layer magnetic steel slot includes a plurality of magnetic steel slot segments. At least two of the plurality of magnetic steel slot segments are arranged in a radial direction of the rotor body and are disposed oppositely at both sides of a direct axis of the rotor body. The outer layer permanent magnet is arranged in the magnetic steel slot segment, a length of the outer permanent magnet disposed in the two oppositely arranged magnetic steel slot segments is L, and a maximum distance between the two oppositely arranged magnetic steel slot segments is C, where 0.8&#xd7;C&#x2264;L.

Rotor structure, permanent magnet auxiliary synchronous reluctance motor and electric vehicle

Disclosed are a rotor structure, a permanent magnet auxiliary synchronous reluctance motor, and an electric vehicle. The rotor structure includes a rotor body; the rotor body is provided with permanent magnet slot groups each including multiple layers of permanent magnet slots; the multiple layers of permanent magnet slots include a first permanent magnet slot; and the first permanent magnet slot includes a first permanent magnet slot section and a first bent slot. A first end of the first bent slot is connected to a second end of the first permanent magnet slot section, a second end of the first bent slot is arranged to extend toward an outer edge of the rotor body.

Growing community of inventors

Shenzhen, China

Hui Huang