• 디지털융복합연구
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• 제15권8호
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• pp.351-357
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• 2017

본 연구는 스마트 폰 음성인식 서비스를 분석하고 음성인식 서비스의 상황별 만족도 조사를 통하여 사용자들의 기대요구와 만족도 간의 관련성을 분석하여 더 나은 음성인식 서비스 발전을 모색하고자 하였다. 1차로 문헌연구를 통하여 음성인식 서비스의 개념과 현황을 알아보고, 2차로 육하원칙을 기조로 한 설문지를 통해 설문 조사를 진행하였다. 그 결과, 사용자는 스마트 폰 음성인식 서비스를 전화를 걸 때에 가장 많이 사용하며, 주로 혼자 있을 때 사용하며 시간대는 대체로 평이하지만, 저녁 시간이 가장 많았다. 또한, 해당 서비스는 집에서 가장 많이 사용하며 손을 사용할 수 없을 때 서비스를 가장 많이 사용하는 것으로 나타났다. 이러한 상황별 다양한 결과를 통해 개인화 서비스, 조건 인식 기능, 위급 상황 자동인식, 음성으로 잠금 해제 등 다양한 방안을 도출할 수 있었다. 본 연구를 바탕으로 추후 국내 스마트 폰 음성인식 서비스 개선과 웨어러블 디바이스 개발을 위해 효과적으로 활용할 수 있을 것으로 기대한다.

• 한국인터넷방송통신학회논문지
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• 제13권2호
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• pp.233-237
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• 2013

이미지 인식은 패턴인식의 중요한 한 연구 분야이다. 본 논문은 이미지 세그멘테이션 알고리즘을 소개하고, 이의 응용으로 도로 Sign 인식시스템에 적용하여 그 결과를 고찰하였다. 본 논문에서, 우리는 이미지 프로세싱 기술의 도움으로 도로 Sign 의 체계적인 연구를 하였고, 이에 해당하는 알고리즘을 만들었다. 도로 Sign을 인식하기 위하여, 본 논문은 이미지 세그멘테이션 알고리즘 파트와 이미지 인식파트의 두 부분으로 나누어서 기술하였다. 인식실험은 도로 Sign 인식 알고리즘 모델이 스마트 폰에 유용하게 사용될 것과, 그 외 여러분야에 사용될 수 있음을 보여 준다.

• 디지털산업정보학회논문지
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• 제15권4호
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• pp.149-157
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• 2019

In case of reading passport using a smart phone in contrast with a dedicated passport reading system, MRZ(Machine Readable Zone) character recognition can be hard when the character strokes were broken, touched or blurred according to the lighting condition, and the position and size of MRZ character lines were varied due to the camera distance and angle. In this paper, the effective recognition algorithm of the passport MRZ information using a combined neural network recognizer of CNN(Convolutional Neural Network) and ANN( Artificial Neural Network), is proposed under the various sized and skewed passport images. The MRZ line detection using connected component analysis algorithm and the skew correction using perspective transform algorithm are also designed in order to achieve effective character segmentation results. Each of the MRZ field recognition results is verified by using five check digits for deciding whether retrying the recognition process of passport MRZ information or not. After we implement the proposed recognition algorithm of passport MRZ information, the excellent recognition performance of the passport MRZ information was obtained in the experimental results for PC off-line mode and smart phone on-line mode.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1072-1075
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• 2005

This paper presents that TD method is applied to the human adaptive devices for smart home with context awareness (or recognition) technique. For smart home, the very important problem is how the appliances (or devices) can adapt to user. Since there are many humans to manage home appliances (or devices), managing the appliances automatically is difficult. Moreover, making the users be satisfied by the automatically managed devices is much more difficult. In order to do so, we can use several methods, fuzzy controller, neural network, reinforcement learning, etc. Though the some methods could be used, in this case (in dynamic environment), reinforcement learning is appropriate. Among some reinforcement learning methods, we select the Temporal Difference learning method as a core algorithm for adapting the devices to user. Since this paper assumes the environment is a smart home, we simply explained about the context awareness. Also, we treated with the TD method briefly and implement an example by VC++. Thereafter, we dealt with how the devices can be applied to this problem.

• International journal of advanced smart convergence
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• 제12권4호
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• pp.119-125
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• 2023

Smart home in the 4th industrial revolution environment is where all devices in the home are connected to each other to provide the optimal living environment desired by the user. Artificial intelligence speakers are being used as a way to manage and control all devices used in this environment. The function of an artificial intelligence speaker ranges from simple music playback to serving as an interface that controls and manages all devices in a smart home space. In this study, we investigated and analyzed the usability of artificial intelligence speakers based on the current status of domestic and overseas markets and the survey contents of two organizations (Korea Consumer Agency and Korea Information and Communication Policy Institute (KISDI)). In addition, we investigated and analyzed the usability of artificial intelligence speakers. Based on the results of responses from users from two related organizations, major problems were derived, and major improvement measures, such as discovering new functions and improving voice recognition performance, were also described.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제6권3호
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• pp.197-201
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• 2006

In the implementation of a smart home, activity recognition technology using simple sensors is very important. In this paper, we propose a new activity recognition method based on Bayesian network (BN). The structure of the BN is learned by K2 algorithm and is composed of sensor nodes, activity nodes and time node whose state is quantized with reasonable interval. In the proposed method, the BN has less complexity and provides better activity recognition rate than the previous method.

• 한국컴퓨터정보학회논문지
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• 제20권9호
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• pp.67-72
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• 2015

Recently, studies that interact with human and things through motion recognition are increasing due to the expansion of IoT(Internet of Things). This paper proposed the system that recognizes the user's logical activity in home environment by attaching some sensors to various objects. We employ Arduino sensors and appreciate the logical activity by using the physical activitymodel that we processed in the previous researches. In this System, we can cognize the activities such as watching TV, listening music, talking, eating, cooking, sleeping and using computer. After we produce experimental data through setting virtual scenario, then the average result of recognition rate was 95% but depending on experiment sensor situation and physical activity errors the consequence could be changed. To provide the recognized results to user, we visualized diverse graphs.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2017년도 춘계학술대회
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• pp.609-610
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• 2017

최근 IoT를 향한 관심이 많아짐에 따라, IoT 기기와 스마트폰을 이용한 서비스가 다양한 산업에 적용되고 있다. 그 중에서 전자 출결 시스템은 여러 기관에서 구축하여 서비스 되고 있으나, 아직 사용자 인식이 정확하지 않다는 문제점이 있다. 본 논문은 기존의 전자 출결 시스템 중 BLE 비콘을 기반으로 한 시스템에서, 사용자 인식 부분의 정확도를 높일 수 있는 상황인지 기반의 사용자 인식방법을 제안한다.

• 대한임베디드공학회논문지
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• 제19권1호
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• pp.27-32
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• 2024

Recently, there has been a growing interest in integrating physical toys into video gaming within the game content business. This paper introduces a novel method that leverages low-cost camera as an alternative to using sensor attachments to meet this rising demand. We address the limitations associated with low-cost cameras and propose an optical design tailored to the specific environment of model car recognition. We overcome the inherent limitations of low-cost cameras by proposing an optical design specifically tailored for model car recognition. This approach primarily focuses on recognizing the underside of the car and addresses the challenges associated with this particular perspective. Our method employs a transfer learning model that is specifically trained for this task. We have achieved a 100% recognition rate, highlighting the importance of collecting data under various camera exposures. This paper serves as a valuable case study for incorporating low-cost cameras into vision systems.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2007년도 가을 학술발표논문집 Vol.34 No.2 (C)
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• pp.516-520
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• 2007

This paper presents a intuitive, simple and easy smart home TV remote control system using the hand gesture recognition. Hand candidate regions are detected by cascading policy of the part of human anatomy on the disparity map image, Exact hand region is extracted by the graph-cuts algorithm using the skin color information. Hand postures are represented by shape features which are extracted by a simple shape extraction method. We use the forward spotting accumulative HMMs for a smart home TV remote control system. Experimental results show that the proposed system has a good recognition rate of 97.33 % for TV remote control in real-time.