• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.5
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• pp.668-674
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• 2022

Machine learning techniques using visual data have high usability in fields of industry and service such as scene recognition, fault detection, security and user analysis. Among these, user analysis through the videos from CCTV is one of the practical way of using vision data. Also, many studies about lightweight artificial neural network have been published to increase high usability for mobile and embedded environment so far. In this study, we propose the network combining the object detection and classification for mobile graphic processing unit. This network detects pedestrian and face, classifies age and gender from detected face. Proposed network is constructed based on MobileNet, YOLOv2 and skip connection. Both detection and classification models are trained individually and combined as 2-stage structure. Also, attention mechanism is used to improve detection and classification ability. Nvidia Jetson Nano is used to run and evaluate the proposed system.

• Journal of the korean academy of Pediatric Dentistry
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• v.49 no.2
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• pp.234-240
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• 2022

Floating-Harbor syndrome (FHS) is a rare genetic disorder. This report introduced in a patient with FHS. Distinctive facial characteristics, severe skeletal class 3 malocclusion with underdeveloped maxilla and protruded mandible, congenital missing teeth, microdontia and ectopic positions of maxillary teeth were presented in the patient. In his twin sister, mild skeletal class 3 malocclusion with protruded mandible was observed but congenital missing teeth and microdontia were not observed. High-arched palate, narrow V-shaped maxillary arch compared to wide and ovoid mandibular arch and inverse relationship between the maxillary and mandibular intermolar width resulted in posterior crossbite were confirmed by model analysis of the patient. These were not observed in the twins. Behaviorally, poor cooperation during dental treatment because of mental retardation was observed in the patient.

• Journal of Platform Technology
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• v.11 no.3
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• pp.56-67
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• 2023

Recently, de-identification of personal information, which has been a long-cherished desire of the data-based industry, was revised and specified in August 2020. It became the foundation for activating data called crude oil[2] in the fourth industrial era in the industrial field. However, some people are concerned about the infringement of the basic rights of the data subject[3]. Accordingly, a development study was conducted on the Batch De-Identification Tool, a personal information de-identification automation tool. In this study, first, we developed an image labeling tool to label human faces (eyes, nose, mouth) and car license plates of various resolutions to build data for training. Second, an object recognition model was trained to run the object recognition module to perform de-identification of personal information. The automated personal information de-identification tool developed as a result of this research shows the possibility of proactively eliminating privacy violations through online services. These results suggest possibilities for data-based industries to maximize the value of data while balancing privacy and utilization.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.3
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• pp.173-178
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• 2022

Recently, various computing technologies such as artificial intelligence, big data, and IoT are developing. In particular, artificial intelligence-based deepfake technology is being used in various fields such as the content and medical industry. Deepfake technology is a combination of deep learning and fake, and is a technology that synthesizes a person's face or body through deep learning, which is a core technology of AI, to imitate accents and voices. This paper uses deepfake technology to study the creation of virtual characters through the synthesis of animation models and real person photos. Through this, it is possible to minimize various cost losses occurring in the animation production process and support writers' work. In addition, as deepfake open source spreads on the Internet, many problems emerge, and crimes that abuse deepfake technology are prevalent. Through this study, we propose a new perspective on this technology by applying the deepfake technology to children's material rather than adult material.

• Journal of Digital Convergence
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• v.10 no.10
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• pp.283-288
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• 2012

3D is the one of the current world in the spotlight as part of the future earnings of the business sector. Existing flat 2D and stereoscopic 3D to change the 3D shape and texture make walking along the dimension of the real world and the virtual reality world by making it feel contemporary reality of coexistence good show. 3D for the interest of the people has been spreading throughout the movie which is based on a 3D Avata. 3D TV market of the current conglomerate of changes in the market pioneer in the 3D market, further leap into the era of the upgrade was. At the same time, however, the modern man of the world, if becoming a necessity in the smartphone craze new innovation in the IT market mobile phone market and also has made. A small computer called a smartphone enough, the ripple velocity and the aftermath of the innovation of the telephone, the Internet as much as to leave many issues. Smartphone smart phone is a mobile phone that can be several functions. The current iPhone, Android. In addition to a large number of Windows Phone smartphones are released. Above the overall prospects of the future and a business service model for 3D facial expression as input avatar virtual 3D character on camera on your smartphone camera to recognize a user's emotional expressions on the face of the person is able to synthetic synthesized avatars in real-time to other mobile phone users matching, transmission, and be able to communicate in real-time sensibility fused video communication services to the development of applications.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.38 no.4
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• pp.311-319
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• 2012

Seborrheic dermatitis (SD) is the skin disease occurred because of Malassezia yeast which grows on the skin and scalp, and this yeast lives on sebum lipid, and their metabolite, free lipid acids are thought to be the main irritant on skin. To find out effective cosmeceutical ingredients to treat SD symptoms, we established novel cell-based in vitro model mimicking SD symptoms. This in vitro model adopted the co-culture system with primary sebocyte & HaCaT keratinocyte. We used M. globosa yeast extract, arachidonic acid, linoleic acid and dihydrotestosterone as SD inducers. In the co-culture system with optimized concentrations for SD-inducing cocktail, the production of IL-8 and sebum lipids increased up to 2-fold, and then we screened with commercial essential oils by monitoring IL-8 as a key inflammatory biomarker. Then we found that Cinnamomum zeylanicum oil, Mentha arvensis oil effectively down-regulated IL-$1{\alpha}$, IL-6, IL-8 cytokines which over-produced by SD-inducing cocktail. Additionally, two essential oils also showed inhibitory effect on sebum lipid synthesis from primary sebocyte and growth inhibitory effect to M. globosa yeast (MICs were lower than 0.0625 %). Our recent results suggest that Cinnamomum zeylanicum oil and Mentha arvensis oil could be effective natural herbal remedies to relieve or protect scalp seborrheic dermatitis.

• Journal of the HCI Society of Korea
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• v.1 no.2
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• pp.43-50
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• 2006

A mirror is a familiar tool for human beings who have been seeing themselves through it for a long time since it was created. As evolving Digital Technology, many approaches about digital mirrors which reflect not only the light, but also the information have been studied. Traditional mirrors on the wall do not need any special control to perform their automatic visual feedbacks, reflecting lights. On the contrary, digital mirrors can actively provide more information to the user than the traditional ones. In this paper, we propose an active digital mirror system of which functions are changed according to the user-mirror distance. First of all, we investigated users' behaviors on mirrors and categorized the interactions by user-mirror distance. Based on the previous result, we designed the user interface of the mirror, and developed a prototype which has three recognition modules: a distance measuring module using infrared sensor arrays, a user recognition module by computer vision technique, and a control perception module using infrared sensor grid. In addition, the next steps for improving the user-centered digital mirror system, and the possibility for developing a mirror-shaped computer system were suggested.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.2
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• pp.149-155
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• 2020

The Korea Highway Traffic Authority provides statistics that analyze the causes of traffic accidents that occurred since 2015 using the Traffic Accident Analysis System (TAAS). it was reported Through TAAS that the driver's forward carelessness was the main cause of traffic accidents in 2018. As statistics on the cause of traffic accidents, 51.2 percent used mobile phones and watched DMB while driving, 14 percent did not secure safe distance, and 3.6 percent violated their duty to protect pedestrians, representing a total of 68.8 percent. In this paper, we propose a system that has improved the advanced driver assistance system ADAS (Advanced Driver Assistance Systems) by utilizing CNN (Convolutional Neural Network) among the algorithms of Deep Learning. The proposed system learns a model that classifies the movement of the driver's face and eyes using Conv2D techniques which are mainly used for Image processing, while recognizing and detecting objects around the vehicle with cameras attached to the front of the vehicle to recognize the driving environment. Then, using the learned visual steering model and driving environment data, the hazard is classified and detected in three stages, depending on the driver's view and driving environment to assist the driver with the forward and blind spots.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2004.11a
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• pp.249-258
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• 2004

오늘날 활발하게 이루어지고 있는 유비쿼터스 컴퓨팅 관련 기술 연구는 사용자가 시간과 장소에 구애받지 않고 네트워크에 접근해 다양한 컴퓨터 관련 서비스를 제공 받을 수 있는 방법에 초점을 맞추고 있다. 이 처럼 시간과 공간의 한계를 뛰어 넘은 네트워크로의 자유로운 접근은 일상 생활의 패러다임을 바꾸어 놓게 될 것이다. 유비쿼터스 컴퓨팅 기술을 통해 가장 큰 변화가 일어나는 분야는 일반 가정환경에서 일어나는 인텔리전트 홈 네트워크 (Intelligent Home Network) 라고 할 수 있다. 집에 들어오면, 자동으로 문을 열어주고, 불을 켜주며, 놓쳤던 TV 프로그램을 자동으로 녹화해 놓았다가 원하는 시간에 보여주고, 적당한 시간에 목욕물을 미리 받아준다. 또한 집밖으로 나가기 전, 일기예보에 따라 우산을 챙겨주고, 일정을 확인시켜주며 입고 나갈 옷을 골라줄 수도 있다. 이 모든 일들이 유비쿼터스 컴퓨팅 기술이 가져올 인텔리전트 홈 네트워크의 모습이다. 그러나, 모든 사용자에게 효과적인 서비스를 제공하기 위해서는 홈 네트워크 상의 자원 관리에서 일어날 수 있는 에이전트들간의 자원 접근 권한 충돌을 효율적으로 방지할 수 있는 기술이 필요하다. 유비쿼터스 컴퓨팅 환경에서 자원관리 특성은 점유의 연속성, 자원 사이의 연관성, 그리고 자원과 사용자 사 사이의 연계성의 3 가지 특성을 지니고 있다. 본 논문에서는 유비쿼터스 컴퓨팅 환경에서 일어날 수 있는 자원 충돌 상황을 효율적으로 처리하기 위한 자원 협상 방법을 제안한다. 본 방법은 자원 관리 특성을 바탕으로 시간논리에 기반을 둔 자원 선점과 분배 규칙으로 구성된다.트 시스템은 b-Cart를 기반으로 할 것으로 예측할 수 있다.타났다. 또한, 스네이크의 초기 제어점을 얼굴은 44개, 눈은 16개, 입은 24개로 지정하여 MER추출에 성공한 영상에 대해 스네이크 알고리즘을 수행한 결과, 추출된 영역의 오차율은 각각 2.2%, 2.6%, 2.5%로 나타났다.해서 Template-based reasoning 예를 보인다 본 방법론은 검색노력을 줄이고, 검색에 있어 Feasibility와 Admissibility를 보장한다.매김할 수 있는 중요한 계기가 될 것이다.재무/비재무적 지표를 고려한 인공신경망기법의 예측적중률이 높은 것으로 나타났다. 즉, 로지스틱회귀 분석의 재무적 지표모형은 훈련, 시험용이 84.45%, 85.10%인 반면, 재무/비재무적 지표모형은 84.45%, 85.08%로서 거의 동일한 예측적중률을 가졌으나 인공신경망기법 분석에서는 재무적 지표모형이 92.23%, 85.10%인 반면, 재무/비재무적 지표모형에서는 91.12%, 88.06%로서 향상된 예측적중률을 나타내었다.ting LMS according to increasing the step-size parameter $\mu$ in the experimentally computed. learning curve. Also we find that convergence speed of proposed algorithm is increased by (B+1) time proportional to B which B is the number of recycled data b

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.41-43
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• 2022

In order to prevent and block infectious diseases caused by the recent COVID-19 pandemic, non-contact biometric information acquisition and analysis technology is attracting attention. The invasive and attached biometric information acquisition method accurately has the advantage of measuring biometric information, but has a risk of increasing contagious diseases due to the close contact. To solve these problems, the non-contact method of extracting biometric information such as human fingerprints, faces, iris, veins, voice, and signatures with automated devices is increasing in various industries as data processing speed increases and recognition accuracy increases. However, although the accuracy of the non-contact biometric data acquisition technology is improved, the non-contact method is greatly influenced by the surrounding environment of the object to be measured, which is resulting in distortion of measurement information and poor accuracy. In this paper, we propose a context-based bio-signal modeling technique for the interpretation of personalized information (image, signal, etc.) for bio-information analysis. Context-based biometric information modeling techniques present a model that considers contextual and user information in biometric information measurement in order to improve performance. The proposed model analyzes signal information based on the feature probability distribution through context-based signal analysis that can maximize the predicted value probability.