• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2014년도 추계학술발표대회
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• pp.1191-1194
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• 2014

본 논문은 스마트 글래스 혹은 스마트 디바이스를 활용해서, 영상을 인식하여 다양한 표현을 할 수 있는 서비스에 대한 것이다. 스마트 글래스를 활용하여 일반 사용자에게 제공할 수 있는 다양한 서비스에 대해서 소개하려고 한다.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2009년도 IWAIT
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• pp.547-550
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• 2009

The object recognition mechanism of human being is not well understood yet. On research of animal experiment using an ape, however, neurons that respond to simple shape (e.g. circle, triangle, square and so on) were found. And Hypothesis has been set up as human being may recognize object as combination of such simple shapes. That mechanism is called Figure Alphabet Hypothesis, and those simple shapes are called Figure Alphabet. As one way to research object recognition algorithm, we focused attention to this Figure Alphabet Hypothesis. Getting idea from it, we proposed the feature extraction algorithm for object recognition. In this paper, we described recognition of binarized images of multifont alphabet characters by the recognition model which combined three-layered neural network in the feature extraction algorithm. First of all, we calculated the difference between the learning image data set and the template by the feature extraction algorithm. The computed finite difference is a feature quantity of the feature extraction algorithm. We had it input the feature quantity to the neural network model and learn by backpropagation (BP method). We had the recognition model recognize the unknown image data set and found the correct answer rate. To estimate the performance of the contriving recognition model, we had the unknown image data set recognized by a conventional neural network. As a result, the contriving recognition model showed a higher correct answer rate than a conventional neural network model. Therefore the validity of the contriving recognition model could be proved. We'll plan the research a recognition of natural image by the contriving recognition model in the future.

• 한국산업정보학회논문지
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• 제15권5호
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• pp.159-166
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• 2010

사회불안, 소득증대, 인구구조 변화, 보안인식 변화로 물리보안은 지속적으로 성장하고 변화되고 있다. 현재 물리보안은 전화망과 방범장비로 구성된 무인방범, DVR과 카메라를 이한 영상보안, 지문인식과 RF카드를 활용한 출입통제가 대표적이다. 하지만, 네트워크 카메라, 생체인식기술, USIM NFC를 활용한 개인인증, 위치기반 서비스 등 ICT기반의 융합으로 산업영역을 확대시켜 나가고 있다. 본 논문에서는 물리보안에 적용할 수 있는 주요 기술동향과 융합보안의 서비스를 개인 신변보호를 위한 개인보안, 대형건물의 다양한 보안 서비스를 제공하는 빌딩 IT 컨버전스, 전방위 보안을 위한 홈랜드 시큐리티로 구분하여 미래의 물리보안 서비스를 제안한다.

• 한국주거학회논문집
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• 제13권3호
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• pp.93-101
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• 2002

The goal of this survey is to propose planning and design informations for the public open spaces in apartment housing, through the observation and analysis of the current situations. For this, the planning information of housing suppliers about public open spaces and the spatial utilization of users were compared and by analyzing facility utilization and resident\`s recognition. This study is also intended to guide the future directions of the research for the improvement of public open spaces. The research follows three phases; \circled1 To understand the conditions of public open spaces in apartment housing sites through survey and analysis of catalogues and references. \circled2 To study on facility utilization and resident's recognition by observation and analysis. \circled3 To propose planning guidelines for the improvement of public open space by recognition differences of facilities.

• Journal of Multimedia Information System
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• 제6권4호
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• pp.185-190
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• 2019

For future autonomous cars, it is necessary to recognize various surrounding environments such as lanes, traffic lights, and vehicles. This paper presents a method of speed sign recognition from a single image in automatic driving assistance systems. The detection step with the proposed method emphasizes the color attributes in modified YUV color space because speed sign area is affected by color. The proposed method is further improved by extracting the digits from the highlighted circle region. A sequential cascade AdaBoost classifier is then used in the recognition step for real-time processing. Experimental results show the performance of the proposed algorithm is superior to that of conventional algorithms for various speed signs and real-world conditions.

• 한국군사과학기술학회지
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• 제20권2호
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• pp.289-299
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• 2017

Because of its unique ordnance or operational requirements, military aircraft has potential risks different from civil aircraft. This explains why there is no global document for military airworthiness and each nation has its own sovereign authority. But harmonized airworthiness activities among authorities are required to reduce cost and time for recent multinational programs. In this study, we show the airworthiness policy of the European Military Airworthiness Authorities and U.S. DOD Authorities which facilitate recognition of certificates and approvals issued by any other authorities. And we propose future works for Korea military airworthiness society to develop organizational recognition system.

• 반도체디스플레이기술학회지
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• 제19권2호
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• pp.96-99
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• 2020

According to brilliant development of smart devices, many related services are being devised. And, almost every service is designed to provide user-centric services based on personal information. In this situation, to prevent unintentional leakage of personal information is essential. Conventionally, ID and Password system is used for the user authentication. This is a convenient method, but it has a vulnerability that can cause problems due to information leakage. To overcome these problem, many methods related to face recognition is being researched. Through this paper, we investigated the trend of user authentication through biometrics and a representative model for face recognition techniques. One is DeepFace of FaceBook and another is FaceNet of Google. Each model is based on the concept of Deep Learning and Distance Metric Learning, respectively. And also, they are based on Convolutional Neural Network (CNN) model. In the future, further research is needed on the equipment configuration requirements for practical applications and ways to provide actual personalized services.

• 한국농촌건축학회논문집
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• 제7권3호
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• pp.27-35
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• 2005

This study is about finding out characteristic of recognition individual housing in seaside of Donghae. To accomplish this purpose, we survey the 150 houses related to the landscape. Thus the major analysis is to take basic data, such as image(modern, western, traditional, etc) about exterior form of housing corresponding to the landscape. The result summarized as follows First, the elements for the characteristic of recognition were exterior material finish, exterior color, roof type, roof material finish, window size, roof slope, area of wall vs roof. Second, the image of traditional housing was very insufficient to plan landscape of housing with design elements. This research suggests that landscape housing of future is to be environmental landscape design and the proper design is to be various considering not only user's preference but also control of landscape.

• 한국멀티미디어학회논문지
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• 제24권5호
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• pp.695-700
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• 2021

The Faster RCNN-based shellfish recognition algorithm is introduced for shellfish recognition studies that currently do not have any deep learning-based algorithms in a practical setting. The original feature extraction module is replaced by DenseNet, which fuses multi-level feature data and optimises the NMS algorithm, network depth and merging method; overcoming the omission of shellfish overlap, multiple shellfish and insufficient light, effectively solving the problem of low shellfish classification accuracy. In the complexifier test environment, the test accuracy was improved by nearly 4%. Higher testing accuracy was achieved compared to the original testing algorithm. This provides favourable technical support for future applications of the improved Faster RCNN approach to seafood quality classification.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2022년도 봄 학술논문 발표대회
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• pp.229-230
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• 2022

With the development of digital technology, construction companies at home and abroad are in the process of computerizing work and site information for the purpose of improving work efficiency. To this end, various technologies such as BIM, digital twin, and AI-based safety management have been developed, but the accuracy and completeness of the related technologies are insufficient to be applied to the field. In this paper, the learning data that has undergone a pre-processing process optimized for recognition of construction information based on structural members is trained on an existing artificial intelligence model to improve recognition accuracy and evaluate its effectiveness. The artificial intelligence model optimized for the structural member created through this study will be used as a base technology for the technology that needs to confirm the safety of the structure in the future.