Goertek Inc.

Goertek Optical Technology Co., Ltd.

Yifan Zhang

Libing Zou

Jifeng Tian

Jie Liu

Fuli Xie

Fuqiang Zhang

Baoming Li

Xueqiang Wang

Shunran Di

Wenchao Zhang

Yue Ning

Pengcheng Su

Shiyu Li

Xiufeng Song

Guomin Zou

The subject matter provides a path planning method, apparatus and electronic device. Wherein, the method comprises: performing environment modeling according to static road network information and dynamic road condition information of a road network so as to obtain an environment model; determining a plurality of candidate paths according to a starting point and an ending point; extracting from the environment model an environmental feature corresponding to each candidate path by a feature extraction network of a path planning model; inputting the environmental feature to a value estimation network of the path planning model so as to obtain an estimated value for each candidate path output by the value estimation network; determining an optimal path among the candidate paths according to the estimated value.

Path planning method, apparatus and electronic device

A screen defect detection method and apparatus and an electronic device are disclosed. The method comprises the following steps: identifying a number of suspected defective pixel points(S) from a detection image of a target screen; determining a suspected defect region(S) corresponding to a suspected defective pixel point in the detection image; dividing the suspected defect region into a general region and a core region(S); and judging whether the target screen has a transparent defect(S) according to a mean gray value of the suspected defect region, a mean gray value of the general region and a minimum gray value of the core region.

Screen defect detection method, apparatus, and electronic device

The present application discloses a method for filtering image feature points and a terminal. The method for filtering image feature points includes: providing quality score values to feature points extracted from an image, and according to the feature points and the quality score values of the feature points, training a neural-network model; after one time of filtering has started up, acquiring one frame of an original image and extracting feature points in the original image; inputting the original image and the feature points in the original image into the neural-network model, obtaining and outputting quality score values corresponding to the feature points in the original image; and according to the quality score values, filtering the feature points in the original image. The method for filtering image feature points can improve the success rate of the matching of the feature points in relocated application scenes, thereby improving the locating efficiency.

Method for filtering image feature points and terminal

A multi-AGV motion planning method, device and system are disclosed. The method of the present disclosure comprises: establishing an object model through reinforcement learning; building a neural network model based on the object model, performing environment settings including AGV group deployment, and using the object model of the AGV in a set environment to train the neural network model until a stable neural network model is obtained; setting an action constraint rule; and after the motion planning is started, inputting the state of current AGV, states of other AGVs and permitted actions in a current environment into the neural network model after trained, obtaining the evaluation indexes of a motion planning result output by the neural network model, obtaining an action to be executed of the current AGV according to the evaluation indexes, and performing validity judgment on the action to be executed using the action constraint rule.

Multi-AGV motion planning method, device and system

The present application discloses a method and device for updating a map. The method for updating a map according to the present embodiment includes: in a process of movement of a robot, when it is detected that an actual environment is different from an environment that is indicated by a global map that has already been established, starting up map updating, and establishing an initial local map; determining a locating point according to acquired sensor data and the global map, and optimizing the initial local map according to the locating point, to obtain an optimized local map; and covering a corresponding area of the global map by using the optimized local map, to complete updating of the global map. The embodiments of the present application improve the locating accuracy, ensure the speed and efficiency of the map updating, and save time.

Method and device for updating map

A character defect detection method and device are disclosed. The character defect detection method comprises: acquiring an image to be inspected containing a character and a template character image corresponding to the character, and converting the image to be inspected into an image having a format consistent with a format of the template character image; extracting a first valid area containing the character from the image to be inspected, and extracting a second valid area containing a template character from the template character image; obtaining a first image based on the first valid area, and obtaining a second image based on the second valid area; calculating a transformed image indicating an information difference between the first image and the second image based on the first image and the second image; and obtaining a character defect detection result of the image to be inspected based on information of the transformed image.

Character defect detection method and device

A computer vision-based anomaly detection method and device and an electronic apparatus are disclosed. The method comprises: dividing a target picture into at least two feature regions according to different region features of the target picture, and forming training sets respectively using the feature regions corresponding to each target picture; selecting generative adversarial networks GAN as network models to be used, and training GAN network models with the training sets of different feature regions to obtain GAN network models corresponding to different feature regions; and when performing anomaly detection, performing same feature region division on a target picture to be detected, inputting different feature regions of the target picture to be detected into corresponding GAN network models to obtain a generated picture, and performing pixel value-based difference detection on the generated picture and the target picture to be detected.

Computer vision-based anomaly detection method, device and electronic apparatus

A method and device for small sample defect classification and a computing equipment are disclosed. The method comprises: separating a target to be tested into parts, and segmenting an original image of the target to be tested into at least two sub-images containing different parts according to the separated parts; establishing small sample classification models with respect to each sub-image and the original image respectively, and obtaining a classification result of each sub-image and a classification result of the original image by using corresponding classification models, wherein the classification result includes a defect category and a corresponding category probability; and determining and outputting a defect category of the target to be tested according to classification results of all the sub-images and the original image.

Method and device for small sample defect classification and computing equipment

A global path planning method and device for an unmanned vehicle are disclosed. The method comprises: establishing an object model through a reinforcement learning method, wherein the object model includes: a state of the unmanned vehicle, an environmental state described by a map picture, and an evaluation index of a path planning result; building a deep reinforcement learning neural network based on the object model established, to obtain a stable neural network model; inputting the map picture of the environment state and the state of the unmanned vehicle into the deep reinforcement learning neural network after trained, and generating a motion path of the unmanned vehicle. According to the present disclosure, the environment information in the scene is marked through the map picture, and the map features are extracted through the deep neural network, thereby simplifying the modeling process of the map scene.

Global path planning method and device for an unmanned vehicle

The present disclosure discloses a method and device for optimizing an object-class model based on a neural network. The method includes: establishing the object-class model based on the neural network, training the object-class model, and realizing classification of target images by using the object-class model that has been trained; and when a new target image is generated, and the new target image is an image corresponding to a new condition of a target and is capable of still being classified into an original classification system, judging a result of identification of the object-class model to the new target image, and if the object-class model is not capable of correctly classifying the new target image, according to the new target image, selecting some of parameters, adjusting the some of parameters, and training to obtain an object-class model that is capable of correctly classifying the new target image.

Method and device for optimizing object-class model based on neural network

A multi-screen display system and a mouse switching control method are disclosed. The mouse switching control method is applied to a multi-screen display system comprising a main display screen and at least one extended display screen, and comprises: obtaining user images collected by cameras installed on the main display screen and the extended display screen respectively; inputting the user images into a neural network model, and predicting a screen that a user is currently paying attention to using the neural network model to obtain a prediction result; and controlling to switch a mouse to the screen that a user is currently paying attention to according to the prediction result. The system and mouse switching control method are based on self-learning of visual attention, predict the current screen operated by the user, automatically switch the mouse to the corresponding screen position, and improve the user experience.

Multi-screen display system and mouse switching control method thereof

A product defect detection method, device and system are disclosed. The method comprises: acquiring a sample image of a product, extracting candidate image blocks probably including a product defect from the sample image, and extracting preset shape features corresponding to the candidate image blocks and texture features corresponding to the candidate image blocks; training a first-level classifier using the preset shape features to obtain a first-level classifier that can further screen out target image blocks probably including a product defect from the candidate image blocks; training a second-level classifier using the texture features to obtain a second-level classifier that can correctly identify a product defect; and when performing product defect detection, inputting preset shape features of candidate image blocks extracted from a product image into the first-level classifier, and then inputting texture features of obtained target image blocks into the second-level classifier to detect a defect in the product.

Product defect detection method, device and system

The application discloses a method for monitoring a user gesture and a wearable device. The method comprises: providing an inertial sensor in a wearable device, the wearable device being located on the head of a user when being worn; monitoring movement data of the head of the user in real time, by using the inertial sensor, when the user is wearing the wearable device; conducting gesture solving by using the movement data to obtain gesture data of the head of the user; determining whether a head gesture of the user is a correct gesture according to the gesture data and a preset strategy; and sending a reminder to the user when the head gesture of the user is an incorrect gesture.

Method for monitoring user gesture of wearable device

A product defect detection method, device and system are disclosed. The method comprises: constructing a defect detection framework including segmentation networks, a concatenating network and a classification network, and setting a quantity of the segmentation network according to product defect types, wherein each segmentation network corresponds to a defect type; concatenating the sample image with the mask image output by each segmentation network by using the concatenating network to obtain a concatenated image; training the classification network by using the concatenated images to obtain a classification network capable of correctly identifying a product defect and a defect type; and when performing product defect detection, inputting a product image acquired into the defect detection framework, and detecting a product defect and a defect type existing in the product by using the segmentation networks, the concatenating network and the classification network.

A method and a device for a black and white screen display based on an Android platform, and a smart terminal. The method comprises: selecting a size of the black and white screen according to an image display size that is generated in the Android platform, so that the image display size is adapted to the size of the black and white screen; acquiring Android display data that is generated in the Android platform; individually converting the Android display data that is corresponding to each of pixels into black and white display data that is corresponding to each of the pixels; buffering the converted black and white display data into a queue, extracting the data from the queue by using a preset real-time process and outputting to a data interface of the black and white screen according to a preset frame rate; and displaying the black and white display data that is corresponding to each of the pixels on the black and white screen.

Growing community of inventors

Weifang, China

Yifan Zhang