• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.1718-1721
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• 1997

An image processing algorithm is developed in order to recognize the type of cars, the position of a number plate and the characters on the plate. to recognize the type of cars, comparison of two images is used. One has a car image, the other is just a background image without car. After that recognition, a vertical line filter is used to find the location of the plate. Finally the simularity mehod is used to recognize the numbers on plates.

• 한국대기환경학회지
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• 제34권5호
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• pp.735-747
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• 2018

Rainfall depth is an important meteorological information. Generally, high spatial resolution rainfall data such as road-level rainfall data are more beneficial. However, it is expensive to set up sufficient Automatic Weather Systems to get the road-level rainfall data. In this paper, we propose to use deep learning to recognize rainfall depth from road surveillance videos. To achieve this goal, we collect a new video dataset and propose a procedure to calculate refined rainfall depth from the original meteorological data. We also propose to utilize the differential frame as well as the optical flow image for better recognition of rainfall depth. Under the Temporal Segment Networks framework, the experimental results show that the combination of the video frame and the differential frame is a superior solution for the rainfall depth recognition. The final model is able to achieve high performance in the single-location low sensitivity classification task and reasonable accuracy in the higher sensitivity classification task for both the single-location and the multi-location case.

• 한국멀티미디어학회논문지
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• 제19권3호
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• pp.612-619
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• 2016

Applying evolved IT technology to increase the satisfaction of the consumer is a typical feature of the rapidly transformed service industry. Smart devices have taken a place as the mainstream of major media, moreover, IT service strategies utilizing smart devices have been constantly developed. Location recognition method of users has been proposed as one of the significant features to the IT service industry. The long-term care home services can be one example of user location recognition methods that real time computerization of service record utilize an attached tag to home of pensioners with RFID reader or an NFC function of mobile when a home carer provides service. And, the Homecare Electronics Management System (HEMS) and the various location recognition methods will be discussed to improve effectiveness of services. In this paper, we propose a home applicable electronic management system which insurer, home care service facilities, home cares, pensioners and guardians which enables to simultaneously check service records based on the improved system by use of iBeacon.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2008년도 하계종합학술대회
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• pp.1211-1212
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• 2008

In this paper, we propose image process modeling as a part of location based surveillance system for unauthorized target recognition and tracking in harbor, airport, military zone. For this, we compress and store background image in lower resolution and perform object extraction and motion tracking by using sobel edge detection and difference picture method between real images and a background image. In addition to, we use Independent Component Analysis Neural Network for moving target recognition. Experiments are performed for object extraction and tracking of moving targets on road by using static camera in 20m height building and it shows the robust results.

• Journal of Electrical Engineering and Technology
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• 제1권1호
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• pp.35-41
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• 2006

This paper presents a new numerical algorithm for fault location estimation and for faults recognition based on the synchronized phasors. The proposed algorithm is based on the synchronized phasor measured from the synchronized PMUs installed at two-terminals of the transmission lines. In order to discriminate the fault type, the arc voltage wave shape is modeled numerically on the basis of a great number of arc voltage records obtained by transient recorder. From the calculated arc voltage amplitude it can make a decision whether the fault is permanent or transient. The results of the proposed algorithm testing through computer simulation are given.

• 대한의용생체공학회:의공학회지
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• 제28권4호
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• pp.494-502
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• 2007

Ubiquitous location based services (u-LBS) will be interested to an important services. They can easily recognize object position at anytime, anywhere. At present, many researchers are making a study of the position recognition and tracking. This paper consists of postion recognition and user identification system. The position recognition is based on location under services (LBS) using a signal strength map, a database is previously made use of empirical measured received signal strength indicator (RSSI). The user identification system automatically controls instruments which is located in home. Moreover users are able to measures body signal freely. We implemented the multi-hop routing method using the Star-Mesh networks. Also, we use the sensor devices which are satisfied with the IEEE 802.15.4 specification. The used devices are the Nano-24 modules in Octacomm Co. Ltd. A RSSI is very important factor in position recognition analysis. It makes use of the way that decides position recognition and user identification in narrow indoor space. In experiments, we can analyze properties of the RSSI, draw the parameter about position recognition. The experimental result is that RSSI value is attenuated according to increasing distances. It also derives property of the radio frequency (RF) signal. Moreover, we express the monitoring program using the Microsoft C#. Finally, the proposed methods are expected to protect a sudden death and an accident in home.

• 인터넷정보학회논문지
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• 제12권6호
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• pp.73-82
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• 2011

지금까지의 위치인식 환경은 사람이나 사물 또는 이동체 자체에 대해서만 연구되어 왔다. 그러나 본 연구에서는 주행 중인 차량에 있는 여러 탑승자의 위치를 실시간으로 식별하고 추적하는 서비스에 대한 위치인식 모델을 제안하였다. 탑승자의 위치를 식별하려면 GPS기능이 탑재된 고가형 단말기를 이용하는 경우와 GPS기능이 없는 저가형 소형단말기를 이용하는 경우로 구분할 수 있다. 본 연구에서는 단순한 소형단말기가 GPS를 탑재한 차량용 인터페이스와 센서네트워크로 메시지를 전송하게 함으로써 탑승상황에 따른 효율적인 위치인식을 제공하도록 하였다. 이 기법은 먼저 차량의 상태(정차, 주행)를 감지하고, 주행상태라면 탑승자가 탑승이나 하차를 할 수 없기 때문에 굳이 위치정보를 송수신할 필요가 없어 트래픽을 감소시킬 수 있다. 이것은 전력소모를 줄여 배터리 수명을 늘릴 수 있도록 한다. 이에 본 연구에서는 제안한 차량정차 감지알고리즘을 탑승자 위치추적 시스템으로 구현하여 그 효용성을 확인하기 위해 실험하였다. 또한 설계하여 구현한 시스템을 이용하여 실험한 결과 최대수신거리는 12m로 측정되었으며, 200회의 실험을 통해 탑승인식과 하차인식이 모두 성공했음을 알 수 있었다. 또한 주행인식 측정실험에서는 차량정차 알고리즘을 적용한 경우가 그렇지 않은 경우에 비해서 41.6%의 전송트래픽을 감소시킬 수 있었다.

• 한국주거학회:학술대회논문집
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• 한국주거학회 2006년도 추계학술발표대회 논문집
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• pp.248-252
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• 2006

This study is intended to understand the intrinsic attributes of the view from the apartment unit in consideration of the diverse and complex elements of the view. To this end, the Questionnaire survey was conducted to identify the tendency in the recognition by apartment dwellers. The Questionnaire survey was conducted for the apartment residents to identify their interest in and the general trend in their recognition of the view from the living rooms of their housing unit, where Questionnaire items regarding landscape elements, the distances to and location of the landscape elements, and floor locations were compiled on the basis of the results from the field survey in the previous study. Consequently, the following results have been derived. 1) Apartment residents recognize not only natural landscape elements but also artificial elements, and prefer natural elements to artificial ones. 2) It is also indicated that they recognize the distances to and locations of landscape elements and that the satisfaction for the distance and location varies depending on the type of the landscape elements. 3) Furthermore, the floor of each unit is shown to result in certain differences in the recognized landscape elements. The cross-analysis between the floor and satisfaction indicates that the higher the floor, the more satisfied the residents are with the view.

• 한국멀티미디어학회논문지
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• 제25권6호
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• pp.807-818
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• 2022

In order to further improve the accuracy and time efficiency of behavior recognition in intelligent monitoring scenarios, a human behavior recognition algorithm based on YOLO combined with LSTM and CNN is proposed. Using the real-time nature of YOLO target detection, firstly, the specific behavior in the surveillance video is detected in real time, and the depth feature extraction is performed after obtaining the target size, location and other information; Then, remove noise data from irrelevant areas in the image; Finally, combined with LSTM modeling and processing time series, the final behavior discrimination is made for the behavior action sequence in the surveillance video. Experiments in the MSR and KTH datasets show that the average recognition rate of each behavior reaches 98.42% and 96.6%, and the average recognition speed reaches 210ms and 220ms. The method in this paper has a good effect on the intelligence behavior recognition.

• 한국전자통신학회논문지
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• 제11권8호
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• pp.759-766
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• 2016

본 논문은 비정상 상황 시 발생하는 음원에 대해 주변 환경 음에 강인한 음원 구간을 검출하여, 구간내의 신호를 이용한 음원 인식 과 위치 추적 시스템 설계에 관한 연구이다. 강인한 음원 구간 검출은 수신되는 오디오 신호로부터 단 구간 가중 평균 델타 에너지를 계산하여, 저역 통과 필터에 입력 후, 출력되는 결과 값들의 비교를 통해 배경음에 강인한 구간을 정의 하며, 음원 인식은 검출된 구간 내 데이터로부터 종래의 인식 방법인 HMM(: Hidden Markov Model)을 이용해, 음원 인식 정보를 생성하여 학습 및 인식을 한다. 이는 주변 배경음이 포함된 음원 신호에 대해 기존 신호의 에너지를 이용해 구간을 검출 후, HMM을 통한 인식에 비해 3.94% 상향된 인식률을 보인다. 또한 인식 결과를 바탕으로 구간내의 신호간의 TDOA(: Time Delay of Arrival)를 이용한 위치 파악은 실제 발생 위치와의 각도와 97.44%일치함을 보인다.