公开(公告)号：US20240320981A1

公开(公告)日：2024-09-26

申请号：US18044551

申请日：2021-09-08

Applicant: 42DOT INC.

Inventor： Seung Jae LEE ,  Aidyn ZHAKATAYEV ,  Seong Gyun JEONG

IPC: G06V20/56 ,  G06T7/11 ,  G06V10/44

CPC classification number: G06V20/56 ,  G06T7/11 ,  G06V10/44

Abstract: An embodiment provides an apparatus for determining a vehicle boarding possible area for a driving image using a artificial neural network, including: an image segmentation module that obtains a driving image for a driving direction of a vehicle from a camera module and segments the driving image into a plurality of image strips; a pre-trained boarding availability classification artificial neural network module that uses the image strip as input information and boarding availability information for the image strip as output information; a feature extraction module that extracts an activation map including feature information on the image strip from the boarding availability classification artificial neural network module; and an area information generation module that generates boarding possible area information for the image strip based on the feature information included in the activation map.

公开(公告)号：US20230326219A1

公开(公告)日：2023-10-12

申请号：US18044381

申请日：2021-09-07

Applicant: 42DOT INC.

Inventor： Seung Jae LEE ,  Aidyn ZHAKATAYEV ,  seong Gyun JEONG

IPC: G06V20/56 ,  G06V10/82 ,  G06V10/776 ,  G06V10/774 ,  G08G1/16 ,  G01C21/36

CPC classification number: G06V20/588 ,  G06V10/82 ,  G06V10/776 ,  G06V10/774 ,  G08G1/167 ,  G01C21/3602

Abstract: An embodiment provides a lane determination apparatus for a driven vehicle using an artificial neural network comprising an image information collection module configured to acquire driving image information of a vehicle from at least one camera module installed in the vehicle, a pre-trained lane prediction artificial neural network module, with the driving image information as input information and with lane prediction information of the vehicle and confidence information for the lane prediction information as output information, an output information distribution calculation module configured to calculate a data distribution map of the output information to thereby generate a first data distribution map, a reference information distribution calculation module configured to collect reference information for actual traveling lane prediction information of the vehicle, to calculate a data distribution map of the reference information, and to thereby generate a second data distribution map and a confidence calibration module configured to update parameters of the artificial neural network module so as to reduce a difference between the first data distribution map and the second data distribution map based on the second data distribution map.