• Proceedings of the Korean Information Science Society Conference
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• 2003.10b
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• pp.22-24
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• 2003

최근 웹 확산에 따른 일반인들의 인터넷 이용이 급증하였고 이에 따른 정보 기술도 빠르게 변화하고 있다. GIS 분야에서도 시대의 흐름에 맞춰 공간 데이타를 웹상에서 제공하는 웹 GIS 분야가 등장하게 되었다. 그러나, 상호이질적인 공간 데이타를 웹 기반 분산 환경에서 서비스하기 위해 표준 인터페이스와 각각의 웹 서비스 모델을 정의한 통합 시스템이 요구되고 있다. OGC에서는 기존 OPenGIS의 상호운용성을 웹 환경에서 지원하고, 또한 피쳐 인스턴스 단위의 지리정보를 접근하기 위해 새로운 웹 피쳐 서비스 구현 명세를 제안하였다. 웹 피쳐 서비스 구현 명세에서는 클라이언트로부터 HTTP를 통하여 요청된 공간.비공간 질의를 처리하기 위한 URL 컴포넌트를 정의하고 있다. 이 컴포넌트는 클라이언트 질의를 수행하여 피쳐 인스턴스 단위로 데이타를 검색 및 조작하고, 검색된 데이타는 GML로 정의하여 클라이언트로 제공한다. 본 논문에서는 OGC가 제안한 XML 기반의 표준 공간 데이타 포맷인 GML과 웹 피쳐 서비스 인터페이스를 이용해 분산된 지리정보 데이타를 웹 브라우저를 통하여 서비스할 수 있는 웹 피쳐 서비스 시스템을 설계 및 구현하였다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2021.06a
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• pp.7-9
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• 2021

본 논문은 Detectron2 [1]에서 지원하는 객체 검출 임무 수행 네트워크의 과정 중에서 추출한 피쳐 맵을 신경망 기반으로 압축하는 방법을 제안한다. 이를 위해, 신경 망 기반 영상 압축을 지원하는 공개 소프트웨어인 CompressAI [2] 모델 중 하나인 bmshj2018-hyperprior 의 압축 네트워크를 활용하여 임무 수행 네트워크의 과정 중 스탬 레이어(stem layer)에서 추출된 피쳐 맵을 압축하도록 학습시켰다. 또한, 압축 네트워크의 입력 피쳐 맵의 너비와 높이 크기가 64 의 배수가 되도록 객체 검출 네트워크의 입력 영상 보간 값을 조정하는 방법도 제안한다. 제안하는 신경망 기반 피쳐 맵 압축 방법은 피쳐 맵을 최근 표준이 완료된 차세대 압축 표준 방법인 VVC(Versatile Video Coding, [3])로 압축한 결과에 비해 큰 성능 향상을 보이고, VCM 앵커와 유사한 성능을 보인다.

• KIISE Transactions on Computing Practices
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• v.23 no.11
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• pp.625-631
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• 2017

The stock price prediction for stock markets remains an unsolved problem. Although there have been various overtures and studies to predict the price of stocks scientifically, it is impossible to predict the future precisely. However, stock price predictions have been a subject of interest in a variety of related fields such as economics, mathematics, physics, and computer science. In this paper, we will study fluctuation patterns of stock prices and predict future trends using the Deep learning. Therefore, this study presents the three deep learning models using Tensorflow, an open source framework in which each learning model accepts different input features. We expand the previous study that used simple price data. We measured the performance of three predictive models increasing the number of priced-based input features. Through this experiment, we measured the performance change of the predictive model depending on the price-based input features. Finally, we compared and analyzed the experiment result to evaluate the impact of the price-based input features in stock price prediction.

• Annual Conference on Human and Language Technology
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• 2023.10a
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• pp.39-43
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• 2023

자동 음성 인식(Automatic Speech Recognition, ASR)은 컴퓨터가 인간의 음성을 텍스트로 변환하는 기술이다. 자동 음성 인식 시스템은 다양한 응용 분야에서 사용되며, 음성 명령 및 제어, 음성 검색, 텍스트 트랜스크립션, 자동 음성 번역 등 다양한 작업을 목적으로 한다. 자동 음성 인식의 노력에도 불구하고 노인 음성 인식(Elderly Speech Recognition, ESR)에 대한 어려움은 줄어들지 않고 있다. 본 연구는 노인 음성 인식에 콘포머(Conformer)와 피쳐 퓨전 모듈(Features Fusion Module, FFM)기반 노인 음성 인식 모델을 제안한다. 학습, 평가는 VOTE400(Voide Of The Elderly 400 Hours) 데이터셋으로 한다. 본 연구는 그동안 잘 이뤄지지 않았던 콘포머와 퓨전피쳐를 사용해 노인 음성 인식을 위한 딥러닝 모델을 제시하였다는데 큰 의미가 있다. 또한 콘포머 모델보다 높은 수준의 정확도를 보임으로써 노인 음성 인식을 위한 딥러닝 모델 연구에 기여했다.

• The Journal of the Korea Contents Association
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• v.13 no.1
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• pp.1-8
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• 2013

The accuracy of a real facial recognition system can be varied according to the accuracy of the eye detection algorithm when we design and implement a semi-automatic facial recognition algorithm depending on the eye position of a database. In this paper, a fully automatic facial recognition algorithm is proposed such that Gabor and LBP features are extracted from fiducial points of a face graph which was created by using fiducial points based on the eyes, nose, mouth and border lines of a face, fitted on the face image. In this algorithm, the recognition performance could be increased because a face graph can be fitted on a face image automatically and fiducial points based LPB features are implemented with the basic Gabor features. The simulation results show that the proposed algorithm can be used in real-time recognition for more than 1,000 faces and produce good recognition performance for each data set.

• Journal of the Korea Society of Computer and Information
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• v.13 no.7
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• pp.37-49
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• 2008

Services are reusable units in business level. Ubiquitous computing provides computing services anytime and anywhere. The combination of both is becoming an important paradigm of computing environment. Fundamentals of services require flexibility and interoperability, and key elements of ubiquitous modeling require interoperability and context-awareness. There are two kinds of methods to identify services. The top-down approach is based on business process, and the bottom-up approach is based on components. The first approach depends on experts' intuitions, while the second approach suffers the incapability of expressing non-functional expression through components. Although a feature-based approach is capable of expressing non-functional expression and identifying services in ubiquitous environment, the research on this issue is not adequately addressed by far. To promote this research, this paper proposes a feature-based method to identify services in ubiquitous computing. The method extracts initial-candidate-services from a feature model. Then, the ultimate services are identified through optimizing and analyzing the candidate-services. The proposed method is expected to enhance the service reusability by effectively analyzing ubiquitous domain based on feature, and varying reusable service units.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2013.06a
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• pp.317-318
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• 2013

International Hydrography Organization has published S-100 Universal Hydrographic Data Model to support use of various hydrographic data for navigational safety. In the S-100 standards, it is possible to manage hydrographic data and apply various application field by introducing the concept of registry and its register. In this study, the S-100 standard based product specification in the field of maritime safety is developed by designing application schema according to general feature model defined in the S-100 standard, and feature catalogue is produced through simple registry.

• The Journal of the Korea Contents Association
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• v.11 no.2
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• pp.31-39
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• 2011

The facial recognition algorithms using Gabor wavelet based face graph produce very good performance while they have some weakness such as a large amount of computation and an irregular result depend on initial location. We proposed a fully automatic facial recognition algorithm using a Gabor feature based geometric deformable face graph matching. The initial location and size of a face graph can be selected using Adaboost detection results for speed-up. To find the best face graph with the face model graph by updating the size and location of the graph, the geometric transformable parameters are defined. The best parameters for an optimal face graph are derived using an optimization technique. The simulation results show that the proposed algorithm can produce very good performance with recognition rate 96.7% and recognition speed 0.26 sec for FERET database.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.13-22
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• 2021

The clinical decision support system uses accumulated medical data to apply an AI model learned by machine learning to patient diagnosis and treatment prediction. However, the existing black box-based AI application does not provide a valid reason for the result predicted by the system, so there is a limitation in that it lacks explanation. To compensate for these problems, this paper proposes a system model that applies XAI that can be explained in the development stage of the clinical decision support system. The proposed model can supplement the limitations of the black box by additionally applying a specific XAI technology that can be explained to the existing AI model. To show the application of the proposed model, we present an example of XAI application using LIME and SHAP. Through testing, it is possible to explain how data affects the prediction results of the model from various perspectives. The proposed model has the advantage of increasing the user's trust by presenting a specific reason to the user. In addition, it is expected that the active use of XAI will overcome the limitations of the existing clinical decision support system and enable better diagnosis and decision support.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.3
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• pp.316-322
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• 2014

A movie recommendation system is proposed to learn a preference model of a viewer by using multimodal features of a video content and their evoked implicit responses of the viewer in synchronized manner. In this system, facial expression, body posture, and physiological signals are measured to estimate the affective states of the viewer, in accordance with the stimuli consisting of low-level and affective features from video, audio, and text streams. Experimental results show that it is possible to predict arousal response, which is measured by electrodermal activity, of a viewer from auditory and text features in a video stimuli, for estimating interestingness on the video.