• 국방과기술
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• 12호통권274호
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• pp.46-53
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• 2001

미래 전쟁에 대비하기 위하여, 미국은 합동참모본부의 Joint Vision 2020에서 정보에서의 우월성을 기초로 압도적인 기동, 정확한 공격, 집중된 군수지원, 전면적인 방어를 이룩하여 전체적인 우위전력 확보를 도모하여, 정보에서의 우월성 확보를 위해 $C^4ISR$(Command, Control, Communication and Computer, Intelligence, Surveillance, Reconnaissance)개념에 의한 통합체계의 구축을 목표로 제시하고 있다.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2000년도 추계학술대회논문집 - 한국공작기계학회
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• pp.68-73
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• 2000

This study to embody automatic recognition of VIN(Vehicle Identification Number)character by computer vision system. Automatic recognition characters methods consist of the thining processing and the recognition of each character. VIN character and background classified using counting method of the size of connected pixels. Thining processing applied to segmentation of connected fundamental phonemes by Hilditch's algorithm. Each VIN character contours tracing algorithm used the Freeman's direction tracing algorithm.

• 국방과기술
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• 1호통권275호
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• pp.58-67
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• 2002

미래 전쟁에 대비하기 위하여, 미국은 합동참모본부의 Joint Vision 2020에서 정보에서의 우월성을 기초로 압도적인 기동, 정확한 공격, 집중된 군수지원, 전면적인 방어를 이룩하여 전체적인 우위전력 확보를 도모하며, 정보에서의 우월성 확 보 를 위 해 $C^4ISR$(Command, Control, Communication and Computer, Intelligence, Surveillance, Reconnaissance) 개념에 의한 통합체계의 구축을 목표로 제시하고 있다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2012년도 춘계학술발표대회
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• pp.1007-1009
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• 2012

고혈압과 같은 만성질환 환자들은 약물치료 외에도 운동, 식습관 조절등과 생활습관 개선을 위해 꾸준한 자가관리가 필요하다. 본 논문은 최근 대중적으로 보급되고 있는 스마트폰을 통해 이러한 고혈압 환자들의 자가관리를 돕기 위한 프로그램을 개발하고자 한다.

• 우주기술과 응용
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• 제1권1호
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• pp.104-120
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• 2021

Some optical schemes of lenses for spacecraft developed by the author are considered. The main optical characteristics of telescope lenses of various architectures are compared. We propose compact solutions of mirror, lens-mirror, and lens systems with maximum available angular resolutions and other parameters. Examples of calculating the optical systems of lenses used for various tasks both in the field of astronomy and in the field of remote sensing of the Earth and other planets are given. The example of onboard computer system is discussed. Practical recommendations on the development and use of telescope lenses are given.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2018년도 춘계학술대회
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• pp.143-144
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• 2018

일반적으로 개인용 컴퓨터를 조작하기 위하여 사용자는 시각과 손을 사용해야 한다. 시각과 손이 불편한 대부분 장애우들은 개인용 컴퓨터를 조작하기 매우 어려우며 장애우를 보조하기 위한 장치들은 가격이 비싼 문제가 있다. 이 논문에서는 아마존 에코를 이용하여 음성으로 개인용 컴퓨터를 조작하기 위한 시스템을 제안한다. 제안한 시스템은 설계한 스킬이 저장된 아마존 웹 서버에서 개인용 컴퓨터로 접근하여 개인용 컴퓨터의 마우스를 제어하고 이를 이용하여 응용 프로그램을 조작한다.

• 제어로봇시스템학회논문지
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• 제17권11호
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• pp.1168-1172
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• 2011

Beam projector is popularly used for presentation. In order to pay attention to local area of the beam projector display, a laser pointer is used together with a pointing device(Mouse). Simple wireless presenter has limited functions of a pointing device such as "go to next slide" or "back to previous slide" in a specific application(Microsoft PowerPoint) through wireless channel; thus, there is inconvenience to do other tasks e.g., program execution, maximize/minimize window etc. provided by clicking mouse buttons. The main objective of this paper is to implement a multi-functional laser-pointer mouse that has the same functions of a computer mouse. In order to get position of laser spot in the projector display, an image processing to extract the laser spot in the camera image is required. In addition, we propose a transformation of the spot position into computer display coordinates to execute mouse functions on computer display.

• 산업기술연구
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• 제38권1호
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• pp.41-52
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• 2018

Recently, object detection is a critical function for any system that uses computer vision and is widely used in various fields such as video surveillance and self-driving cars. However, the conventional methods can not detect the objects clearly because of the dynamic background change in the beach. In this paper, we propose a new technique to detect humans correctly in the dynamic videos like shores. A new background modeling method that combines spatial GMM (Gaussian Mixture Model) and temporal GMM is proposed to make more correct background image. Also, the proposed method improve the accuracy of people detection by using SVM (Support Vector Machine) to classify people from the objects and KCF (Kernelized Correlation Filter) Tracker to track people continuously in the complicated environment. The experimental result shows that our method can work well for detection and tracking of objects in videos containing dynamic factors and situations.

• International Journal of Computer Science & Network Security
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• 제24권3호
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• pp.113-124
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• 2024

One of the goals of the Saudi Arabia 2030 vision is to ensure full employment of its citizens. Recruitment of graduates depends on the quality of skills that they may have gained during their study. Hence, the quality of education and ensuring that graduates have sufficient knowledge about the in-demand skills of the market are necessary. However, IT graduates are usually not aware of whether they are suitable for recruitment or not. This study builds a prediction model that can be deployed on the web, where users can input variables to generate predictions. Furthermore, it provides data-driven recommendations of the in-demand skills in the Saudi IT labor market to overcome the unemployment problem. Data were collected from two online job portals: LinkedIn and Bayt.com. Three machine learning algorithms, namely, Support Vector Machine, k-Nearest Neighbor, and Naïve Bayes were used to build the model. Furthermore, descriptive and data analysis methods were employed herein to evaluate the existing gap. Results showed that there existed a gap between labor market employers' expectations of Saudi workers and the skills that the workers were equipped with from their educational institutions. Planned collaboration between industry and education providers is required to narrow down this gap.

• Journal of Electrical Engineering and Technology
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• 제10권4호
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• pp.1910-1914
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• 2015

Human posture recognition is an attractive and challenging topic in computer vision due to its promising applications in the areas of personal health care, environmental awareness, human-computer-interaction and surveillance systems. Human posture recognition in video sequences consists of two stages: the first stage is training and evaluation and the second is deployment. In the first stage, the system is trained and evaluated using datasets of human postures to ‘teach’ the system to classify human postures for any future inputs. When the training and evaluation process is deemed satisfactory as measured by recognition rates, the trained system is then deployed to recognize human postures in any input video sequence. Different classifiers were used in the training such as Multilayer Perceptron Feedforward Neural networks, Self-Organizing Maps, Fuzzy C Means and K Means. Results show that supervised learning classifiers tend to perform better than unsupervised classifiers for the case of human posture recognition.