公开(公告)号：US20180024798A1

公开(公告)日：2018-01-25

申请号：US15531633

申请日：2016-07-04

Applicant: Goertek Inc.

Inventor： Guomin ZOU ,  Yifan ZHANG ,  Pengcheng SU

IPC: G06F3/14 ,  G09G3/34

CPC classification number: G06F3/14 ,  G09G3/2092 ,  G09G3/34 ,  G09G5/028 ,  G09G2340/08

Abstract: A method and a device for a black and white screen display based on an Android platform, and a smart terminal are disclosed. The method comprising: 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 are generated in the Android platform; individually converting the Android display data that are corresponding to each of pixels into black and white display data that are 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 are corresponding to each of the pixels on the black and white screen.

公开(公告)号：US20220309635A1

公开(公告)日：2022-09-29

申请号：US17309306

申请日：2020-10-24

Applicant: GOERTEK INC.

Inventor： Fuli XIE ,  Yifan ZHANG ,  Jie LIU ,  Jifeng TIAN

IPC: G06T7/00 ,  G06T7/11 ,  G06T3/40

Abstract: 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.

公开(公告)号：US20220254146A1

公开(公告)日：2022-08-11

申请号：US17595079

申请日：2020-10-30

Applicant: GOERTEK INC.

Inventor： Libing ZOU ,  Yifan ZHANG ,  Baoming LI ,  Yue NING

IPC: G06V10/774 ,  G06V10/46 ,  G06N3/08

Abstract: 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.

公开(公告)号：US20220196414A1

公开(公告)日：2022-06-23

申请号：US17593618

申请日：2019-10-24

Applicant: GOERTEK INC.

Inventor： Xueqiang WANG ,  Yifan ZHANG ,  Libing ZOU ,  Baoming LI

IPC: G01C21/34 ,  G05B13/02

Abstract: 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.

公开(公告)号：US20220113420A1

公开(公告)日：2022-04-14

申请号：US17309923

申请日：2020-10-24

Applicant: GOERTEK INC.

Inventor： Yue NING ,  Yifan ZHANG ,  Libing ZOU ,  Fuqiang ZHANG

IPC: G01S17/89 ,  G06N20/20

Abstract: A plane detection method and device based on a laser sensor are disclosed. The method includes: acquiring data of the laser sensor after starting detection; inputting the data into a detection model trained in advance, wherein the detection model is obtained by training with data corresponding to a medium type selected in advance and is capable of recognizing the medium type selected; judging whether an object to which the data belongs is a plane, and if the object is a plane, determining the medium type of the plane; and setting corresponding optimization methods for different medium types, and optimizing the data according to the medium type. The laser sensor recognizes the medium type by the machine learning model, and optimizes the two-dimensional laser data according to the recognition results, and thus forms a more refined map and performs more accurate positioning based on the two-dimensional laser data.