• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.13-16
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• 2024

온라인상에 인간의 감성을 담은 리뷰 데이터가 꾸준히 축적되어왔다. 이 텍스트 데이터를 분석하고 활용하는 일은 마케팅에 있어서 중요한 자산이 될 것이다. 이와 관련된 Aspect-Based Sentiment Analysis(ABSA) 연구는 한글에 있어서는 데이터 부족을 이유로 거의 선행연구가 없는 실정이다. 본 연구에서는 최근 공개된 데이터 셋을 바탕으로 하여 화장품 도메인에 대한 소비자들의 리뷰 텍스트와 사전 라벨링 된 속성, 감성 극성을 기반으로 ABSA를 진행한다. Klue RoBERTa base 모델을 활용하여 데이터를 학습시키고, Python Kiwipiepy 등으로 전처리한 결과를 대시보드로 시각화하여 분석하기 쉬운 환경을 마련하는 방법을 제시한다.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.9
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• pp.96-105
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• 2015

This paper proposes a DSP optimization solution of rain detection and removal algorithm. We propose rain detection and removal algorithms considering camera motion, and also presents optimization results in algorithm level and DSP level. At algorithm level, this paper utilizes a block level binary pattern analysis, and reduces the operation time by using the fast motion estimation algorithm. Also, the algorithm is optimized at DSP level through inter memory optimization, EDMA, and software pipelining for real-time operation. Experiment results show that the proposed algorithm is superior to the other algorithms in terms of visual quality as well as processing speed.

• Journal of Drive and Control
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• v.20 no.4
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• pp.92-99
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• 2023

Autonomous vehicles should recognize and respond to the specified speed to drive in compliance with regulations. To recognize the specified speed, the most representative method is to read the numbers of the signs by recognizing the speed signs in the front camera image. This study proposes a method that utilizes YOLO-Labeling-Labeling-EfficientNet. The sign box is first recognized with YOLO, and the numeric digit is extracted according to the pixel value from the recognized box through two labeling stages. After that, the number of each digit is recognized using EfficientNet (CNN) learned with the virtual environment dataset produced directly. In addition, we estimated the depth of information from the height value of the recognized sign through regression analysis. We verified the proposed algorithm using the virtual racing environment and GTSRB, and proved its real-time performance and efficient recognition performance.

• The KIPS Transactions:PartD
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• v.13D no.1 s.104
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• pp.125-132
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• 2006

The existing recognition system of license plates cannot get the satisfactory result in noise environments. The purpose of this paper is to propose an algorithm that can recognize the region of license plates accurately in a noise environment. The algorithm is formulated by reorganizing the U- and V-channels of YUV color space as YUV is insensitive to light and carries less data than RGB color information. The region of license plates has been extracted by the geometric characteristics, sizes, and places of labeling images. The proposed algorithm was found to improve the process of extracting the region of license plates in various noise environments.

• Journal of Advanced Navigation Technology
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• v.17 no.1
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• pp.98-106
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• 2013

In this paper, we propose a moving object detection and tracking method for multi-view camera environment. Based on the similarity and characteristics of motion vectors and coding block modes extracted from compressed bitstreams, validation of moving blocks, labeling of the validated blocks, and merging of neighboring blobs are performed. To continuously track objects for temporary stop, crossing, and overlapping events, a window based object updating algorithm is proposed for single- and multi-view environments. Object detection and tracking could be performed with an acceptable level of performance without decoding of video bitstreams for normal, temporary stop, crossing, and overlapping cases. The rates of detection and tracking are over 89% and 84% in multi-view environment, respectively. The rates for multi-view environment are improved by 6% and 7% compared to those of single-view environment.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.1
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• pp.129-136
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• 2018

In this paper, we propose a new real-time lane detection method that is efficient for road environment. Existing methods have a problem of low reliability under environmental changes. In order to overcome this problem, we emphasize the lane candidate area by using gray level division. And Extracts a straight line component near the lane by using the Hough transform, and generates an ROI for each straight line based on the extracted coordinates. And integrates the generated ROI images. Then, the lane is determined by dividing the object using the dual queue in the ROI image. The proposed method is able to detect lanes even in the environmental change unlike the conventional method. And It is possible to obtain an advantage that the area corresponding to the background such as sky, mountain, etc. is efficiently removed and high reliability is obtained.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.267-267
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• 2015

가상수의 흐름을 보다 가시적으로 파악하기 위하여 대두된 개념이 물발자국(water footprint)이다. 이는 흔히 사용되고 있는 생태발자국(ecological footprint)이나 탄소발자국(carbon footprint)에 착안하여 도입된 개념으로 한 국가의 물발자국은 직 간접적으로 물건이나 재화를 생산하는데 국민이 소비하는 물의 총량으로 정의된다. 물발자국을 내적/외적으로 단순히 구분하여 산정하는 방식이 진화하여 1단위의 생산에서 유통 및 서비스까지 확대하여 그 전 과정을 모두 포함하는 물발자국 산정방식이 도입된 것은 최근의 일이다. 직접적인 물사용과 간접적인 물사용을 구분하여 물발자국을 산정하고, 그 위에 물의 성질에 따라 green water, blue water, 그리고 grey water로 각각 개념을 상세화하여 물발자국을 산정하는 방안이 도입되었다. 2009년 물발자국 산정의 표준화를 위한 스위스의 제안이 ISO에 제출되었고, 각 국가들에 의한 투표가 진행되어 2010년 물발자국 국제표준안이 채택되었다. 본 연구는 이러한 국제기구에 의한 일련의 국제표준화 작업을 대상으로 진행되었다. 2014년 ISO/TC 207 국제총회가 개최되어 환경경영시스템(SC1), 환경감사(SC2), 환경 라벨링(SC3), 환경성과평가(SC4), 전과정평가(SC5), 온실가스관리(SC7)의 6개 분과위원회(Sub-Committees)가 구성되어 세부논의가 진행되었으며, 이러한 과정을 분석함으로서 물발자국 국제표준(ISO 14046)과 향후 우리나라의 대응방안을 고찰하였다. 물발자국 국제표준(ISO 14046) 제정을 통해 물발자국의 필요성 및 중요성에 대한 국가 간 합의는 도출되었으나, 적용시기 및 세부적인 방법론 등에 대한 이견이 여전히 존재하고 있다. ISO 14046의 실질적 적용에 필요한 세부사항과 관련된 기술보고서 작업초안(WD 14073)은 작업반(SC5/WG8)에서 진행되고 있다. 그러나 물발자국 국제표준이 국가 간 무역장벽이나 특정국의 진입을 막는 수단으로 사용될 수 있는 점 등 실질적으로 국제표준의 도입에 따른 문제점 역시 존재한다. 본 연구에서 제시된 국제표준의 도입 방안을 통하여 가상수무역의 국제적 선점효과를 기대함과 동시에 수자원의 유효한 활용을 기대할 수 있을 것이다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.607-610
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• 2021

When learning a model in supervised learning, input data and the label of the data are required. However, labeling is high cost task and if automated, there is no guarantee that the label will always be correct. In the case of supervised learning in such a noisy labels environment, the accuracy of the model increases at the initial stage of learning, but decrease significantly after a certain period of time. There are various methods to solve the noisy label problem. But in most cases, the probability predicted by the model is used as the pseudo label. So, we proposed a method to predict the true label more quickly by refining the probabilities predicted by the model. Result of experiments on the same environment and dataset, it was confirmed that the performance improved and converged faster. Through this, it can be applied to methods that use the probability distribution predicted by the model among existing studies. And it is possible to reduce the time required for learning because it can converge faster in the same environment.

• Journal of Korea Multimedia Society
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• v.12 no.11
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• pp.1557-1562
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• 2009

In the hydraulic room of a forging press machine, a system which can detect and prevent risks at its early stage is needed because there may be a leakage due to the damage of the connection parts of the piping which can endanger human life and mechanical damage. In this paper, the system to automatically recognize a leakage of hydraulic fluid in terms of using the pan/tilt camera from a remote place is implemented. It finds the bounding boxes which are recognized with object regions in the process of labeling and detects the proper leakage regions of hydraulic fluid with the ratios of width and height of the bounding boxes and compactness of the leakage shape. Also, it performs noise removal and calibration for transition and rotation of image as a preprocessing process. The experimental results show that the proposed system has been verified to detect the leakage regions accurately in various sources of light.

• The Journal of the Korea Contents Association
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• v.7 no.12
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• pp.311-321
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• 2007

For fast and robust face detection, this paper proposes an approach for face detection using fusion of heterogeneous template matching. First, we detect skin regions using a model of skin color which covers various illumination and races. After reducing a search space by region labelling and filtering, we apply template matching with skin color and edge to the detected regions. Finally, we detect a face by finding the best choice of template fusion. Experimental results show the proposed approach is more robust in skin color-like environments than with a single template matching and is fast by reducing a search space to face candidate regions. Also, using a global accumulator can reduce excessive space requirements of template matching.