Hon Hai Precision Industry Co., Ltd.

Hong-fu Jin Precision Industry (shenzhen) Co., Ltd.

Fu Tai Hua Industry (shenzhen) Co., Ltd.

Huawei Technologies Co., Limited

Tencent Technology (shenzhen) Company Limited

Hong Fu Jin Precision Ind. (shenzhen) Co., Ltd.

Shenzhen Dapu Microelectronics Co., Ltd.

Zijilai Innovative Services Co., Ltd.

Inventergy, Inc.

Tencent Technology Company Limited

Li Jiang

Chih-Kuang Chang

Zhong-Kui Yuan

Dong-Hai Li

Xiao-Guang Xue

Xian-Yi Chen

Zhi-Jun Zou

Yi-Rong Hong

Jian-Hua Liu

Yong-Hong Ding

Yan-Li Li

Xiao-Chao Sun

Hua-Wei Yang

Dong-Sheng Liu

Jia-Jia Chen

Zheng-Cai She

Na Yu

Jiaya Jia

Xiaoyong Shen

Yuwing Tai

Weijun Li

Xiang Chen

Shu Liu

Yu-Hua Xu

Wei-Wen Wu

Lu Qi

An image processing method includes: obtaining an image, and performing feature extraction on the image; generating at least one candidate region of the image, and mapping the at least one candidate region into a feature map of the image, one candidate region including one instance; processing the mapped feature map based on a target network for instance segmentation; and indicating an overall structure of an occluded instance in the image by using a perspective mask, and indicating an invisible part of the occluded instance by using a non-perspective mask, the perspective mask and the non-perspective mask representing a relative occlusion relationship of the occluded instance.

Image processing method, apparatus, and device, and storage medium

A method for predicting logical blocks address (LBA) information, including: receiving, by a Solid State Drive (SSD), a trace sent from a host, wherein the host can acquire the trace in a reusable environment; determining, by the SSD, one or more LBAs received by the SSD according to the trace; obtaining, by the SSD, a distribution of the LBAs by learning the LBAs based on a preset learning algorithm; and predicting, by the SSD, one or more subsequent LBAs based on the distribution of the LBAs. As a result, it can perform heat classification and prediction of the following LBA used in the SSD by means of learning the LBA distribution of the SSD in a certain reusable environment of the host, thus to improve the hit rate of reading and writing and the efficiency of classification of hot and cold data in garbage collection.

Method for predicting LBA information, and SSD

A light-emitting structure includes a base, a light-emitting assembly arranged on the base, a cover configured to be covered over the light-emitting assembly, and a coupling member configured to couple the cover to the base. The light-emitting assembly emits light onto a workpiece to be inspected by an image inspection device. The light-emitting assembly is circular, and a lens of the image inspection device is rotationally coupled to the base.

Light-emitting structure

A light-emitting structure includes two outer shells configured to be joined together to cooperatively define a receiving space therein, a connecting assembly configured to join the two outer shells together, and two light-emitting assemblies coupled to the connecting assembly and configured to emit light inside the receiving space. The two outer shells define a number of viewing holes therein for viewing inside the receiving space. The light-emitting assemblies shine light from a number of different angles inside the receiving space.

Spherical light-emitting structure for inspecting workpiece

In a focus identification method for identifying different focuses of an object, discrete image data is acquired from captured images of an object. The images are captured by a charge coupled device (CCD) in motion of a measurement machine at a predetermined time period. The discrete image data includes definitions of the images and Z-coordinates of the CCD when capturing the images. Maxima and minima of the discrete image data are computed to establish intervals within the discrete image data. The intervals are selected one by one, and a curve is fitted according to the discrete image data at the selected interval. A peak value of the fitted curve is computed as one of focuses of the object when a goodness of fit of the fitted curve meets a predetermined criterion.

Focus identification method, system, and computing device

A measurement machine includes an optical lens and a spectral confocal sensor. An electronic device adjusts a zoom ratio of the lens to be a maximum ratio, and calculates X, Y, Z coordinate differences between the lens center and the sensor center. The electronic device calibrates the X, Y coordinate differences at least twice, to obtain calibrated X, Y coordinate differences. The X, Y differences are replaced by the calibrated X, Y coordinate differences when the calibrated X, Y coordinate differences satisfy first predetermined requirements. The electronic device further calibrates the Z coordinate difference at least twice to obtain a calibrated Z coordinate difference. The Z coordinate difference is replaced by the calibrated Z coordinate difference when the calibrated Z coordinate difference satisfies second predetermined requirements.

Electronic device and method for calibrating spectral confocal sensors

A scanner obtains point-cloud data of adjoining parts of a product. A computing device reads two point-clouds from the point-cloud data, fits two or more lines according to the two point-clouds, selects two lines that have the same ascending direction from the two or more lines, and creates a two-dimensional coordinates system base on the two selected lines. The computing device determines a highest point in each of the two point-clouds based on distances from each point in either of the point-clouds to a corresponding selected line, and determines two nearest points in the two point-clouds. A difference between Y coordinates of the two highest points is determined as a gap-height of two adjoining parts of the product, and a difference between X coordinates of the two nearest points is determined as a gap-width between two adjoining parts.

Electronic device and method for analyzing adjoining parts of a product

Back light source

Light unit

In a method to measure widths of measured parts placed on a platform, a computing device connects to one or more charge coupled device (CCD) cameras. The method controls each of the CCD cameras to capture a digital image from a measured part that is placed near the CCD cameras, obtains the digital image of the measured part from each of the CCD cameras in a predefined order, and obtains a binary expression from the digital image of the measured part. When the measured part is placed in a correct position on the platform, the method further obtains three points from an upper boundary of the measured part in the binary expression and another three points from a lower boundary of the measured part in the binary expression, and calculates width of the measured part according to the obtained six points.

Computing device and method for measuring widths of measured parts

Analyzation of image noise using an electronic device. The electronic device and method operating thereon can obtain an initial image captured by an image capturing device of an image measuring machine using an image capturing card of the electronic device when a lighting device of the image measuring machine is shut down, and magnifies an initial gray value of each pixel in the initial image to obtain an updated image. The electronic device and method operating thereon can further determine whether image noise in the updated image complies with a preset condition by analyzing an updated gray value of each pixel in the updated image, and displays the updated image and analysis results on a display device of the electronic device.

Electronic device and method for analyzing image noise

In a method for processing a point cloud using a computing device, a straight line fitted by the point cloud comprising border points is determined as a benchmark line. An inflection point in the point cloud of the benchmark line is determined. If the vertical distance of the inflection point is not greater than the preset filtration value, needless border points in the point cloud are deleted and a remainder point cloud is obtained. If the vertical distance between the inflection point and the benchmark line is greater than a filtration value, the point cloud is divided into two sub-point clouds, and the one sub-point cloud having border points less than the preset number is deleted, and the other sub-point cloud is set as a remainder point cloud.

System and method for processing a point cloud using a computing device

In a method of a computing device for calibrating light channels, one or more channel options of an illumination selecting unit of the computing device are selected to turn on the one or more light channels of a light source device. A camera unit captures a first image of the light source device. A zone and a serial number of each light channel are marked on the first image. Each channel option of the illumination selecting unit is eliminated. The camera unit captures a second image of the light source device when a light channel is turned off. The first image and the second image are compared, and a correlation between the light channel that is turned off and the eliminated channel option is determined. The serial numbers of the channel options are modified and remapped according to correlations between each light channel and each channel option.

Computing device, storage medium, and method for calibrating light channels of light source device

In a method for identifying border lines of elements on an image of an object using a computing device, a Dynamic Link Library (DLL) name and one or more measuring parameters are received from the computing device. A DLL is obtained according to the received DLL name. Measuring functions of the obtained DLL are provided for selection. A constructed function of the DLL is obtained according to the number and types of the received measuring parameters to transmit the received measuring parameters to a selected measuring function. Coordinates of points on the image are computed according to the received measuring parameters using the selected measuring function, and a border line of an element on the image is fitted according to the coordinates of the points.

Computing device and method for identifying border lines of elements on images of objects

Radiator

Growing community of inventors

Shenzhen, China

Li Jiang