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Convolutional Neural Network를 이용한 주차 차량 자세 추정

Title
Convolutional Neural Network를 이용한 주차 차량 자세 추정
Other Titles
Estimation of Parking Vehicle Position using Convolutional Neural Network
Author
정정주
Keywords
자동 주차; 합성곱 신경망; 자세 추정; 딥러닝; 영상 처리; Autonomous parking; Convolutional Neural Network; Vehicle pose estimation; Deep learning; Image processing
Issue Date
2020-07
Publisher
한국자동차공학회
Citation
2020 한국자동차공학회 춘계학술대회, page. 560-563
Abstract
This paper proposes a technique based on Convolutional Neural Network(CNN) using rear view camera images to estimate the vehicle pose for the target point when parking. Identifying the vehicle’s pose for the target point in autonomous vehicles is a key technology in the automatic parking system. Generally, existing algorithm is used to recognize parking spaces with rear view camera images or rear view camera images and ultrasonic sensors to identify the vehicle’s poses for the target point. In this paper, we present feasibility of the network learned by CNN as AVM images to find out the pose of the vehicle simply. We show the performance that was observed when confirming the root mean squared error of the actual values and the predicted values.
URI
https://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE09418041https://repository.hanyang.ac.kr/handle/20.500.11754/169521
ISSN
2713-7163
Appears in Collections:
COLLEGE OF ENGINEERING[S](공과대학) > ELECTRICAL AND BIOMEDICAL ENGINEERING(전기·생체공학부) > Articles
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