• Title/Summary/Keyword: 무인주행 자동차

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Long Distance Vehicle Recognition and Tracking using Shadow (그림자를 이용한 원거리 차량 인식 및 추적)

  • Ahn, Young-Sun;Kwak, Seong-Woo
    • The Journal of the Korea institute of electronic communication sciences
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    • v.14 no.1
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    • pp.251-256
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    • 2019
  • This paper presents an algorithm for recognizing and tracking a vehicle at a distance using a monocular camera installed at the center of the windshield of a vehicle to operate an autonomous vehicle in a racing. The vehicle is detected using the Haar feature, and the size and position of the vehicle are determined by detecting the shadows at the bottom of the vehicle. The region around the recognized vehicle is determined as ROI (Region Of Interest) and the vehicle shadow within the ROI is found and tracked in the next frame. Then the position, relative speed and direction of the vehicle are predicted. Experimental results show that the vehicle is recognized with a recognition rate of over 90% at a distance of more than 100 meters.

Candidate Word List and Probability Score Guided for Korean Scene Text Recognition (후보 단어 리스트와 확률 점수에 기반한 한국어 문자 인식 모델)

  • Lee, Yoonji;Lee, Jong-Min
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.73-75
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    • 2022
  • Scene Text Recognition is a technology used in the field of artificial intelligence that requires manless robot, automatic vehicles and human-computer interaction. Though scene text images are distorted by noise interference, such as illumination, low resolution and blurring. Unlike previous studies that recognized only English, this paper shows a strong recognition accuracy including various characters, English, Korean, special character and numbers. Instead of selecting only one class having the highest probability value, a candidate word can be generated by considering the probability value of the second rank as well, thus a method can be corrected an existing language misrecognition problem.

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Integrated Management System for Vehicle CCTV Video Using Reverse Tunneling (리버스 터널링을 이용한 차량용 CCTV 영상 통합 관리 시스템)

  • Yang, Sun-Jin;Park, Jae-Pyo;Yang, Seung-Min
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.19 no.5
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    • pp.19-24
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    • 2019
  • The development of ICT technology has a huge impact on the existing closed CCTV security equipment market. With the importance of video data particularly highlighted in areas such as self-driving cars, unmanned vehicles and smart cities, various technologies using video are emerging. In this paper, we proposed a method to transmit videos and metadata as a part of smart city integration, and to solve the traffic, environment and security problems caused in urban life by utilizing the metadata instead of using CCTV videos for simple recording purposes, and reverse tunneling technique was designed and implemented as a method for accessing CCTV videos for vehicles from remote locations. Integrated management of CCTV videos and metadata for vehicles that have been used only for limited purposes in closed environments will enable efficient operation of integrated centers in real time required by smart cities, such as vehicle status check, road conditions and facility management.

The Strategic Positioning of Platform Providers and Automotive Manufacturers in the Forthcoming Smart-car Market (스마트카 산업에서 플랫폼사업자와 완성차업체의 전략적 포지셔닝 분석)

  • Hyun, Jae Hoon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.18 no.10
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    • pp.274-280
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    • 2017
  • The smart-car industry has emerged as the important variable that will decide the future industrial contour of the automotive industry, together with commercialization of electronic vehicles, connected cars, infotainment, telematics, and the autonomous/self-driving car. This study analyzes the strategic position of platform companies and car manufacturers that would determine the future of the smart-car market. The findings of this study show that despite the entry barriers in industrial factors, such as economies of scale, the industrial infrastructure, and global production networks, and technical factors like exclusive head-sector information, car manufacturers may be deprived of their industrial leadership by platform companies with map and user data, big data capabilities, and user interface experience if they lag behind ICT innovation. This insight is based on the emerging importance of software and platforms, and the simplification of car structures, proven by the successful commercialization of electronic vehicles. This study complements existing studies mainly focused on technical aspects of the smart-car industry by examining the strategic dimensions of platform companies and their approach to the future smart-car market by comparing them with existing car manufacturing multinationals.

Color Vision Based Close Leading Vehicle Tracking in Stop-and-Go Traffic Condition (저속주행환경에서 컬러비전 기반의 근거리 전방차량추적)

  • Rho, Kwang-Hyun;Han, Min-Hong
    • The Transactions of the Korea Information Processing Society
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    • v.7 no.9
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    • pp.3037-3047
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    • 2000
  • This paper describes a method of tracking a close leading vehicle by color image processing using the pairs of tail and brake lights. which emit red light and are housed on the rear of the vehicle in stop-and-go traffic condition. In the color image converted as an HSV color model. candidate regions of rear lights are identified using the color features of a pair of lights. Then. the pair of tailor brake lights are detected by means of the geometrical features and location features for the pattern of the tail and brake lights. The location of the leading vehicle can be estimated by the location of the detected lights and the vehicle can be tracked continuously. It is also possible to detect the braking status of the leading vehicle by measuring the change in HSV color components of the pair of lights detected. In the experiment. this method tracked a leading vehicle successfully from urban road images and was more useful at night than in the daylight. The KAV-Ill (Korea Autonomous Vehicle- Ill) equipped with a color vision system implementing this algorithm was able to follow a leading vehicle autonomously at speeds of up to 15km!h on a paved road at night. This method might be useful for developing an LSA (Low Speed Automation) system that can relieve driver's stress in the stop-and-go traffic conditions encountered on urban roads.

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Detection Method for Road Pavement Defect of UAV Imagery Based on Computer Vision (컴퓨터 비전 기반 UAV 영상의 도로표면 결함탐지 방안)

  • Joo, Yong Jin
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.35 no.6
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    • pp.599-608
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    • 2017
  • Cracks on the asphalt road surface can affect the speed of the car, the consumption of fuel, the ride quality of the road, and the durability of the road surface. Such cracks in roads can lead to very dangerous consequences for long periods of time. To prevent such risks, it is necessary to identify cracks and take appropriate action. It takes too much time and money to do it. Also, it is difficult to use expensive laser equipment vehicles for initial cost and equipment operation. In this paper, we propose an effective detection method of road surface defect using ROI (Region of Interest) setting and cany edge detection method using UAV image. The results of this study can be presented as efficient method for road surface flaw detection and maintenance using UAV. In addition, it can be used to detect cracks such as various buildings and civil engineering structures such as buildings, outer walls, large-scale storage tanks other than roads, and cost reduction effect can be expected.

Multi-DNN Acceleration Techniques for Embedded Systems with Tucker Decomposition and Hidden-layer-based Parallel Processing (터커 분해 및 은닉층 병렬처리를 통한 임베디드 시스템의 다중 DNN 가속화 기법)

  • Kim, Ji-Min;Kim, In-Mo;Kim, Myung-Sun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.6
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    • pp.842-849
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    • 2022
  • With the development of deep learning technology, there are many cases of using DNNs in embedded systems such as unmanned vehicles, drones, and robotics. Typically, in the case of an autonomous driving system, it is crucial to run several DNNs which have high accuracy results and large computation amount at the same time. However, running multiple DNNs simultaneously in an embedded system with relatively low performance increases the time required for the inference. This phenomenon may cause a problem of performing an abnormal function because the operation according to the inference result is not performed in time. To solve this problem, the solution proposed in this paper first reduces the computation by applying the Tucker decomposition to DNN models with big computation amount, and then, make DNN models run in parallel as much as possible in the unit of hidden layer inside the GPU. The experimental result shows that the DNN inference time decreases by up to 75.6% compared to the case before applying the proposed technique.

A Review of Structural Batteries with Carbon Fibers (탄소섬유를 활용한 구조용 배터리 연구 동향)

  • Kwon, Dong-Jun;Nam, Sang Yong
    • Applied Chemistry for Engineering
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    • v.32 no.4
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    • pp.361-370
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    • 2021
  • Carbon fiber reinforced polymer (CFRP) is one of the composite materials, which has a unique property that is lightweight but strong. The CFRPs are widely used in various industries where their unique characteristics are required. In particular, electric and unmanned aerial vehicles critically need lightweight parts and bodies with sufficient mechanical strengths. Vehicles using the battery as a power source should simultaneously meet two requirements that the battery has to be safely protected. The vehicle should be light of increasing the mileage. The CFRP has considered as the one that satisfies the requirements and is widely used as battery housing and other vehicle parts. On the other hand, in the battery area, carbon fibers are intensively tested as battery components such as electrodes and/or current collectors. Furthermore, using carbon fibers as both structure reinforcements and battery components to build a structural battery is intensively investigated in Sweden and the USA. This mini-review encompasses recent research trends that cover the classification of structural batteries in terms of functionality of carbon fibers and issues and efforts in the battery and discusses the prospect of structural batteries.

A Study on the Accuracy of GNSS Height Measurement Using Public Control Points (공공기준점을 이용한 GNSS 높이측량 정밀도 분석 연구)

  • WON, Doo-Kyeon;CHOI, Yun-Soo;YOON, Ha-Su;LEE, Won-Jong
    • Journal of the Korean Association of Geographic Information Studies
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    • v.24 no.2
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    • pp.78-90
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    • 2021
  • In order to construct a precision geoid, it has been diversified into land, sea, aviation, and satellite gravity measurement methods, and measurement technology has developed, making it possible to secure high-resolution, high-precision gravity data. The construction of precision geoids can be fast and conveniently decided through GNSS surveys without separate leveling, and since 2014, the National Geographic Information Institute has been developing a hybrid geoid model to improve the accuracy of height surveying based on GNSS. In this study, the results of the GNSS height measurement were compared and analyzed choosing existing public reference points to verify the GNSS height measurement of public surveys. Experiments are conducted with GNSS height measurements and analyzed precision for public reference points on coastal, border, and mountainous terrain presented as low-precision areas or expected-to-be low-precision in research reports. To verify the GNSS height measurement, the GNSS ellipsoid height of the surrounding integrated datum to be used as a base point for the GNSS height measurement at the public datum. Based on the checked integrated datum, the GNSS ellipsoid of the public datum was calculated, and the elevation was calculated using the KNGeoid18 model and compared with the results of the direct level measurement elevation. The analysis showed that the results of GNSS height measurement at public reference points in the coastal, border, and mountainous areas were satisfied with the accuracy of public level measurement in grades 3 and 4. Through this study, GNSS level measurement can be used more efficiently than existing direct level measurements depending on the height accuracy required by users, and KNGeoids 18 can also be used in various fields such as autonomous vehicles and unmanned aerial vehicles.

A Study on the Current State of the Library's AI Service and the Service Provision Plan (도서관의 인공지능(AI) 서비스 현황 및 서비스 제공 방안에 관한 연구)

  • Kwak, Woojung;Noh, Younghee
    • Journal of Korean Library and Information Science Society
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    • v.52 no.1
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    • pp.155-178
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    • 2021
  • In the era of the 4th industrial revolution, public libraries need a strategy for promoting intelligent library services in order to actively respond to changes in the external environment such as artificial intelligence. Therefore, in this study, based on the concept of artificial intelligence and analysis of domestic and foreign artificial intelligence related trends, policies, and cases, we proposed the future direction of introduction and development of artificial intelligence services in the library. Currently, the library operates a reference information service that automatically provides answers through the introduction of artificial intelligence technologies such as deep learning and natural language processing, and develops a big data-based AI book recommendation and automatic book inspection system to increase business utilization and provide customized services for users. Has been provided. In the field of companies and industries, regardless of domestic and overseas, we are developing and servicing technologies based on autonomous driving using artificial intelligence, personal customization, etc., and providing optimal results by self-learning information using deep learning. It is developed in the form of an equation. Accordingly, in the future, libraries will utilize artificial intelligence to recommend personalized books based on the user's usage records, recommend reading and culture programs, and introduce real-time delivery services through transport methods such as autonomous drones and cars in the case of book delivery service. Service development should be promoted.