• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.8
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• pp.1111-1120
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• 2022

Image Capturing is a matter of viewing images and describing images in language. The problem is an important problem that can be solved by keeping, understanding, and bringing together two areas of image processing and natural language processing. In addition, by automatically recognizing and describing images in text, images can be converted into text and then into speech for visually impaired people to help them understand their surroundings, and important issues such as image search, art therapy, sports commentary, and real-time traffic information commentary. So far, the image captioning research approach focuses solely on recognizing and texturing images. However, various environments in reality must be considered for practical use, as well as being able to provide image descriptions for the intended purpose. In this work, we limit the universally available Korean and English image captioning models and text generation techniques for the purpose of image captioning.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.4
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• pp.677-686
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• 2023

In this paper, we study the design and implementation of a smart home outing care system that recognizes the user's purpose of going out and delivers useful information that can help when going out. RSS service data of the Korea Meteorological Administration can be transmitted in real time using ESP8266, and a system that can provide weather information to users after analyzing the data using Arduino MEGA is implemented. Using App Inventor, you can pack the necessary items without forgetting, and you can change the settings according to the desired weather and purpose. The position of the microphone was placed outside to increase awareness by 12%, and the sensitivity of the pressure sensor was set to a maximum of 210 kΩ. If there is an obstacle between the doors, the doors open automatically. An ultrasonic sensor was placed on the ceiling of the drawer to recognize an object within the range of 0.5cm to 10cm to check the existence of an object, and a camera was installed to research a security reinforcement system.

• Proceedings of the ESK Conference
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• 1993.04a
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• pp.111-123
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• 1993

TravTek이란 Travel Technology의 합성어이며, 미래의 여행자들이 차를 사용하여 여행할 때, 보다 편리하고 쾌적한 여행이 될 수 있도록 차에 컴퓨터단말기를 부착하여 현재 주행하고 있는 도로 를 차안에서 화면을 통하여 볼 수 있고, 컴퓨터가 최단경로를 운전자에게 제시하고, 도로의 상황과 여 행정보(즉 호텔, 관공명소, 행사안내등)를 컴퓨터화면으로 나타내고, 그 정보를 컴퓨터음성으로 들려 주는 것등이 TravTek 시스템의 주된 요소들이다. 현재 미국 플로리다주의 올란도시에서 GM회사가 TravTek 시스템을 설치한 차 100대를 가지고 10개의 기관이 합작으로 평가연구중에 있으며, 이 논문에서 다루고자 하는 것은 그중에서 이차의 인간공학적 평가로 제한하고자 한다. 이러한 시스템을 설치한 차 를 타고 여행할 때, 여행자가 과연 얼마나 안락하게 여행할 수 있으며, 도로의 체증현상을 줄이고, 사 고를 예방하며, 차의 설계와 목적이 인간공학적으로 합당한 가를 알아보고자 하는 연구이다. 인간공학적 평가 인자들은 (1) 운전자의 수행도, (2) 사용자 선호도, (3) 사용자 인식, (4) 운행정보등이다. 그리고 컴퓨터음성을 사용하였을 때와 사용하지 않았을 때의 두가지 경우와 (1) 움직이는 컴퓨터 지도를 사용하 였을 때, (2) 단순화 한 도로안내를 사용하였을 때, (3) 컴퓨터 지도를 사용하지 않았을 경우(종이지도 사용)에 관해 위의 4가지 인간공학적 인자들을 평가하고자 한다. 이 연구는 아직도 진행중이라 발표하 고자 하는 논문역시 현재까지의 연구결과를 토대로 발표하는 것이므로 완전한 결론을 내릴 수는 없고, 진행과정의 내용과 토의사항과 잠정적인 결론을 제시하고자 한다.기서 사용된 아이콘에 대해서만 타당한 것으로 이것을 모든 아이콘에 대해 일반화시키기는 어려우나 이후에 행해질 Icon-based User Interface 분야의 많은 연구들의 기초가 될 것이다. 더불어 아이콘과 관련된 많은 요인들(문화적 영향, 아이콘 색깔, 크기, 아이콘의 위치등이 인식에 미치는 영향)에 대해서도 연구가 행해져야 할 것이다. 확인하고 각각의 기능을 분명히 했다.가 수월하게 하였고 메모리를 동적으로 관리할 수 있게 하였다. 또한 기존의 smpl에 디버깅용 함수 및 설비(facility) 제어용 함수를 추가하여 시뮬레이션 프로그램 작성을 용이하게 하였다. 예를 들면 who_server(), who_queue(), pop_Q(), push_Q(), pop_server(), push_server(), we(), wf(), printfct() 같은 함수들이다. 또한 동시에 발생되는 사건들의 순서를 조종하기 위해, 동시에 발생할 수 있는 각각의 사건에 우선순위를 두어 이 우선 순위에 의하여 사건 리스트(event list)에서 자동적으로 사건들의 순서가 결정되도록 확장하였으며, 설비 제어방식에 있어서도 FIFO, LIFO, 우선 순위 방식등을 선택할 수 있도록 확장하였다. SIMPLE는 자료구조 및 프로그램이 공개되어 있으므로 프로그래머가 원하는 기능을 쉽게 추가할 수 있는 장점도 있다. 아울러 SMPLE에서 새로이 추가된 자료구조와 함수 및 설비제어 방식등을 활용하여 실제 중형급 시스템에 대한 시뮬레이션 구현과 시스템 분석의 예를 보인다._3$", chain segment, with the activation energy of carriers from the shal

• Journal of Broadcast Engineering
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• v.24 no.3
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• pp.495-505
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• 2019

Typical algorithms of deep learning include CNN(Convolutional Neural Networks), which are mainly used for image recognition, and RNN(Recurrent Neural Networks), which are used mainly for speech recognition and natural language processing. Among them, CNN is able to learn from filters that generate feature maps with algorithms that automatically learn features from data, making it mainstream with excellent performance in image recognition. Since then, various algorithms such as R-CNN and others have appeared in object detection to improve performance of CNN, and algorithms such as YOLO(You Only Look Once) and SSD(Single Shot Multi-box Detector) have been proposed recently. However, since these deep learning-based detection algorithms determine the success of the detection in the still images, stable object tracking and detection in the video requires separate tracking capabilities. Therefore, this paper proposes a method of combining Kalman filters into deep learning-based detection networks for improved object tracking and detection performance in the video. The detection network used YOLO v2, which is capable of real-time processing, and the proposed method resulted in 7.7% IoU performance improvement over the existing YOLO v2 network and 20 fps processing speed in FHD images.

• The Journal of the Korea Contents Association
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• v.6 no.12
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• pp.105-112
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• 2006

In this study, we propose a simple preprocessing method for classification of basal cell carcinoma (BCC), which is one of the most common skin cancer. The preprocessing step consists of data clipping with a half Hanning window and dimension reduction with principal components analysis (PCA). The application of the half Hanning window deemphasizes the peak near $1650cm^{-1}$ and improves classification performance by lowering the false negative ratio. Classification results with various classifiers are presented to show the effectiveness of the proposed method. The classifiers include maximum a posteriori probability (MAP), k-nearest neighbor (KNN), probabilistic neural network (PNN), multilayer perceptron(MLP), support vector machine (SVM) and minimum squared error (MSE) classification. Classification results with KNN involving 216 spectra preprocessed with the proposed method gave 97.3% sensitivity, which is very promising results for automatic BCC detection.

• Journal of Korean Library and Information Science Society
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• v.51 no.2
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• pp.355-379
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• 2020

Digital Library System(DLS) for the school library is a key access tool for school library materials. The purpose of this study was to find ways to improve the accessibility of materials through analysis of students' information search behavior in DLS. Data were collected through recording of 42 participants' DLS search process, and questionnaire. As a result, the search success rate and search satisfaction were found to be lower when the main purpose of DLS is simple leisure reading, information needs are relatively ambiguous, and when user experiences the complicated situations in the search process. The satisfaction level of search time sufficiency was the highest, and the search result satisfaction was the lowest. Besides, there was a need to improve DLS, such as integrated search of other library collection information, the recommendation of related materials, the print output of collection location, voice recognition through mobile apps, and automatic correction of search errors. Through this, the following can be suggested. First, DLS should complement the function of providing career information by reflecting the demand of education consumers. Second, improvements to DLS functionality to the general information retrieval system level must be made. Third, an infrastructure must be established for close cooperation between school library field personnel and DLS management authorities.

• Journal of Digital Convergence
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• v.19 no.3
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• pp.203-209
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• 2021

In this study, a prototype design model was proposed for developing an online recruitment system through multi-dimensional data crawling and social media analysis, and validates text information and video interview in job application process. This study includes a comparative analysis process through text mining to verify the authenticity of job application paperwork and to effectively hire and allocate workers based on the potential job capability. Based on the prototype system, we conducted performance tests and analyzed the result for key performance indicators such as text mining accuracy and interview STT(speech to text) function recognition rate. If commercialized based on design specifications and prototype development results derived from this study, it may be expected to be utilized as the intelligent online recruitment system technology required in the public and private recruitment markets in the future.