• Title/Summary/Keyword: 지도모델

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High Definition Road Map Object usability Verification for High Definition Road Map improvement (정밀도로지도 개선을 위한 정밀도로지도 객체 활용성 검증)

  • Oh, Jong Min;Song, Yong Hyun;Hong, Song Pyo;Shin, Young Min;Ko, Young Chin
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.38 no.4
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    • pp.375-382
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    • 2020
  • As the 4th Industrial Revolution era in worldwide, interest in autonomous vehicles is increasing. but due to recent safety issues such as pedestrian accidents and car accidents, as a technical model for this, the demand for 3D HD maps (High Definition maps) is increasing in including lanes, road markings, road information, traffic lights and traffic signs etc. However, since some complementary points have been continuously raised according to demand, It is necessary to collect the opinions of institutions and companies utilizing HD maps and to improve HD maps. This study was conducted by utilizing the results of the contest for usability verification of HD Maps hosted by the National Geographic Information Institute and organized by the Spatial Information Industry Promotion Institute. For this study, we researched HD maps' layers and codes for HD maps object usability to improve HD maps, constructed HD maps object usability items accordingly, and contested usability verification of HD maps according to the items The contestants conducted verification and analyzed the results. As a result, the most frequently used code for each layer was the flat intersection, and the code showing the highest usage rate was a safety sign. In addition, the use rate of the sub-section and height obstacles was 16.67% and 8.88%, respectively, showing a low ratio. In order to utilize HD maps in the future, this study is expected to require research to continuously collect opinions from customers and improve data objects and data models that are actually needed by customers.

Strategic Plan for Improvement of Citizen Service using Ubiquitous Technology on Public Area: Geospatial Web based Service (유비쿼터스 기술을 이용한 다중집합장소의 시민서비스 고도화 방안 : 지리공간 웹 기반 서비스 제공을 중심으로)

  • Kang, Young-Ok;Kim, Hee-Won
    • Spatial Information Research
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    • v.16 no.1
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    • pp.79-99
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    • 2008
  • Enterprises as well as central and local governments have tried to apply ubiquitous technology to the actual life on the various types of business and projects. In this paper we develop strategic plan to provide public service on public areas based on needs analysis of public services as well as trend analysis of ubiquitous and web technology. Ubiquitous service model should be based on geospatial web which can incorporate participation and collaboration concepts, as the wire/wireless network system develop rapidly. To achieve this purpose, we suggest the following projects; 1), construction of internet map based on geospatial web technology, 2), development of web contents based on geospatial web, 3), installing ubiquitous equipment, and 4), upgrade Seoul Metropolitan Government's homepage and internet system which can incorporate web 2.0 concepts. Ubiquitous service model should be based on not only development of ubiquitous technology but also needs of consumer such as citizen, enterprises, and public sectors which have an interest in that place. Geospatial web will be the core of development of ubiquitous service models.

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Utilizing Mean Teacher Semi-Supervised Learning for Robust Pothole Image Classification

  • Inki Kim;Beomjun Kim;Jeonghwan Gwak
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.5
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    • pp.17-28
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    • 2023
  • Potholes that occur on paved roads can have fatal consequences for vehicles traveling at high speeds and may even lead to fatalities. While manual detection of potholes using human labor is commonly used to prevent pothole-related accidents, it is economically and temporally inefficient due to the exposure of workers on the road and the difficulty in predicting potholes in certain categories. Therefore, completely preventing potholes is nearly impossible, and even preventing their formation is limited due to the influence of ground conditions closely related to road environments. Additionally, labeling work guided by experts is required for dataset construction. Thus, in this paper, we utilized the Mean Teacher technique, one of the semi-supervised learning-based knowledge distillation methods, to achieve robust performance in pothole image classification even with limited labeled data. We demonstrated this using performance metrics and GradCAM, showing that when using semi-supervised learning, 15 pre-trained CNN models achieved an average accuracy of 90.41%, with a minimum of 2% and a maximum of 9% performance difference compared to supervised learning.

Development of Korean Peninsula VS30 Map Based on Proxy Using Linear Regression Analysis (일반선형회귀분석을 이용한 프락시 기반 한반도 VS30지도 개발)

  • Choi, Inhyeok;Yoo, Byeongho;Kwak, Dongyoup
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.42 no.1
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    • pp.35-44
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    • 2022
  • The VS30 map is used as a key variable for site amplification in the ShakeMap, which predicts ground motion at any site. However, no VS30 map considering Korean geology and geomorphology has been developed yet. To develop a proxy-based VS30 map, we used 1,101 VS profiles obtained from a geophysical survey and collected proxy layers of geological and topographical information for the Korean Peninsula. Then, VS30 prediction models were developed using linear regression analysis for each geological age considering the distribution of VS30. As a result, models depending on geomorphology were suggested per each geologic group, including Quaternary, Fill, Ocean, Mesozoic group and Precambrian. Resolution of map is doubled from that of VS30 map by U.S. Geological Survey (USGS). Standard deviation of residual in natural log of proxy-based VS30 map is 0.233, whereas standard deviation of slope-based USGS VS30 map is 0.387. Therefore, the proxy-based VS30 map developed in this study is expected to have less uncertainty and to contribute to predicting more accurately the ground motion amplitude.

The Representation Techniques based on 3D Map to Obtain User-interested Information from Spatio-Temporal Table (시-공간 정보도표상의 사용자 관심정보 획득을 위한 3차원 지도 기반 가시화기법)

  • Lee Seok Jun;Jung Gi Sook;Jeong Seung Dae;Jung Soon Ki
    • Proceedings of the Korean Information Science Society Conference
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    • 2005.11a
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    • pp.751-753
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    • 2005
  • 다양한 과학 분야와 공학 분야에서는 그들이 다루고 있는 특정한 주제의 정보를 좀 더 신속하고, 명확하게 사용자에게 전달하기 위해서 여러 가지 정보가시화(information visualization) 기법을 사용한다. 정보를 가시화 할 때는 기본적으로 세 가지 과정을 거치는데, 원천 데이터(raw data)로부터 데이터 모델(data model)로 변환하고, 변환된 데이터 모델을 가시화 구조상(visual structure)에 매핑(mapping)시킨 후 정보화 모델(information model)로 변환하게 된다. 본 논문에서는 특정 행사가 진행되고 있는 건물내부에서 발생하는 시간, 공간적인 정보를 정리한 도표 메타포(metaphor)를 토대로, 해당 데이터 모델로부터 추출한 다양한 정보를 3차원 지도로 구성된 정보화 모델 상에 반영하기 위한 방법을 제안하였다. 또한, 정보를 단순히 공간상에 반영하기 보다는 사용자의 관심영역(interest area)에 따른 정보의 공간적 의미에 중점을 두어 3차원 공간상에 표현하였다.

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Face Detection Using Multiple Filters and Hybrid Neural Networks (다중 필터와 복합형 신경망을 이용한 얼굴 검출 기법)

  • Cho, Il-Gook;Park, Hyun-Jung;Kim, Ho-Joon
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2005.11a
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    • pp.191-194
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    • 2005
  • 본 논문에서는 방송 영상에서 조명효과와 크기변화 등에 강인한 얼굴패턴 검출기법을 제시한다. 제안된 얼굴검출 모델은 영상 전처리 과정과 얼굴패턴 검출 과정으로 이루어진다. 전처리 과정은 조명변화에 대한 보정기능과 다중필터에 의한 후보영역 선별기능으로 구분된다. 얼굴패턴 검출과정은 다단계의 특징지도 생성과정과 패턴분류 과정으로 이루어진다. 특징지도를 생성하기 위하여 가보(Gabor) 필터계층을 포함하는 CNN(Convolutional Neural Networks)모델을 도입하였다. 다양한 배경을 고려한 효과적인 학습을 위하여 본 논문에서는 억제성의 뉴런(Inhibitory neuron)을 포함하는 구조의 CNN모델을 적용한다. CNN으로부터 추출되는 특징집합은 최종 단계에서 WFMM(Weighted Fuzzy Min Max) 모델을 사용하여 분류된다. 이때 사용되는 특징집합의 크기는 분류기의 규모 및 계산량의 결정적인 역할을 준다. 이에 본 연구에서는 최종 분류 과정에 사용되는 특징의 수를 효과적으로 줄이기 위해 FMM모델을 사용하는 적응적인 특징 선별 기법을 제안한다. 또한 실제 영상을 통한 실험결과로부터 제안된 이론의 타당성을 고찰한다.

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Contrastive Learning of Sentence Embeddings utilizing Semantic Search through Re-Ranker of Cross-Encoder (문장 임베딩을 위한 Cross-Encoder의 Re-Ranker를 적용한 의미 검색 기반 대조적 학습)

  • Dongsuk Oh;Suwan Kim;Kinam Park;Heuiseok Lim
    • Annual Conference on Human and Language Technology
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    • 2022.10a
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    • pp.473-476
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    • 2022
  • 문장 임베딩은 문장의 의미를 고려하여 모델이 적절하게 의미적인 벡터 공간에 표상하는 것이다. 문장 임베딩을 위해 다양한 방법들이 제안되었지만, 최근 가장 높은 성능을 보이는 방법은 대조적 학습 방법이다. 대조적 학습을 이용한 문장 임베딩은 문장의 의미가 의미적으로 유사하면 가까운 공간에 배치하고, 그렇지 않으면 멀게 배치하도록 학습하는 방법이다. 이러한 대조적 학습은 비지도와 지도 학습 방법이 존재하는데, 본 논문에서는 효과적인 비지도 학습방법을 제안한다. 기존의 비지도 학습 방법은 문장 표현을 학습하는 언어모델이 자체적인 정보를 활용하여 문장의 의미를 구별한다. 그러나, 하나의 모델이 판단하는 정보로만 문장 표현을 학습하는 것은 편향적으로 학습될 수 있기 때문에 한계가 존재한다. 따라서 본 논문에서는 Cross-Encoder의 Re-Ranker를 통한 의미 검색으로부터 추천된 문장 쌍을 학습하여 기존 모델의 성능을 개선한다. 결과적으로, STS 테스크에서 베이스라인보다 2% 정도 더 높은 성능을 보여준다.

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Automatic Generation of 3D Building Models using a Draft Map (도화원도를 이용한 3차원 건물모델의 자동생성)

  • Kim, Seong-Joon;Min, Seong-Hong;Lee, Dong-Cheon;Park, Jin-Ho;Lee, Im-Pyeong
    • Journal of Korean Society for Geospatial Information Science
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    • v.15 no.2 s.40
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    • pp.3-14
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    • 2007
  • This study proposes an automatic method to generate 3D building models using a draft map, which is an intermediate product generated during the map generation process based on aerial photos. The proposed method is to generate a terrain model, roof models, and wall models sequentially from the limited 3D information extracted from an existing draft map. Based on the planar fitting error of the roof corner points, the roof model is generated as a single planar facet or a multiple planar structure. The first type is derived using a robust estimation method while the second type is constructed through segmentation and merging based on a triangular irregular network. Each edge of this roof model is then projected to the terrain model to create a wall facet. The experimental results from its application to real data indicates that the building models of various shapes in wide areas are successfully generated. The proposed method is evaluated to be an cost and time effective method since it utilizes the existing data.

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Development of a Screening Method for Deforestation Area Prediction using Probability Model (확률모델을 이용한 산림전용지역의 스크리닝방법 개발)

  • Lee, Jung-Soo
    • Journal of the Korean Association of Geographic Information Studies
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    • v.11 no.2
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    • pp.108-120
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    • 2008
  • This paper discusses the prediction of deforestation areas using probability models from forest census database, Geographic information system (GIS) database and the land cover database. The land cover data was analyzed using remotely-sensed (RS) data of the Landsat TM data from 1989 to 2001. Over the analysis period of 12 years, the deforestation area was about 40ha. Most of the deforestation areas were attributable to road construction and residential development activities. About 80% of the deforestation areas for residential development were found within 100m of the road network. More than 20% of the deforestation areas for forest road construction were within 100m of the road network. Geographic factors and vegetation change detection (VCD) factors were used in probability models to construct deforestation occurrence map. We examined the size effect of area partition as training area and validation area for the probability models. The Bayes model provided a better deforestation prediction rate than that of the regression model.

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Study on Applicability of Nonproportional Model for Teaching Second Graders the Number Concept (초등학교 2학년 수 개념 지도를 위한 비비례모델의 적용 가능성 탐색)

  • Kang, Teaseok;Lim, Miin;Chang, Hyewon
    • Journal of Elementary Mathematics Education in Korea
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    • v.19 no.3
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    • pp.305-321
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    • 2015
  • This study started with wondering whether the nonproportional model used in unit assessment for 2nd graders is appropriate or not for them. This study aims to explore the applicability of the nonproportional model to 2nd graders when they learn about numbers. To achieve this goal, we analyzed elementary mathematics textbooks, applied two kinds of tests to 2nd graders who have learned three-digit numbers by using the proportional model, and investigated their cognitive characteristics by interview. The results show that using the nonproportional model in the initial stages of 2nd grade can cause some didactical problems. Firstly, the nonproportional models were presented only in unit assessment without any learning activity with them in the 2nd grade textbook. Secondly, the size of each nonproportional model wasn't written on itself when it was presented. Thirdly, it was the most difficult type of nonproportional models that was introduced in the initial stages related to the nonproportional models. Fourthly, 2nd graders tend to have a great difficulty understanding the relationship of nonproportional models and to recognize the nonproportional model on the basis of the concept of place value. Finally, the question about the relationship between nonproportional models sticks to the context of multiplication, without considering the context of addition which is familiar to the students.