• Korean Journal of Artificial Intelligence
• /
• v.8 no.2
• /
• pp.11-16
• /
• 2020

Among the innovative companies leading the era of the 4th industrial revolution, the world's largest Internet company is Google. Google has grown by providing convenient services such as Internet search, Android smartphone operating system, and video. Now, Google is leading the global IT industry by continuing to develop in various new business fields based on open service platforms, artificial intelligence, and big data. In this study, an exploratory discussion was conducted on Google's success factors and future directions. The purpose of the research is to understand the development process of the IT field from the successfactors of Google and to analyze the development direction of the future IT industry. Google's success factors were its open platform policy and successful acquisitions of external companies. In fact, most of the services Google offers come from companies that have acquired and acquired them. In addition, there was a corporate culture that values and supportsthe spirit of challenge and autonomy of members who are not afraid of failure. Based on this study's review of Google's direction analysis, the follow-up study will infer the direction of the IT industry in depth and look at the future technologies that IT majors need to prepare.

• Journal of information and communication convergence engineering
• /
• v.22 no.2
• /
• pp.109-120
• /
• 2024

Trash or garbage is one of the most dangerous health and environmental problems that affect pollution. Pollution affects nature, human life, and wildlife. In this paper, we propose modern solutions for cleaning the environment of trash pollution by enforcing strict action against people who dump trash inappropriately on streets, outside the home, and in unnecessary places. Artificial Intelligence (AI), especially Deep Learning (DL), has been used to automate and solve issues in the world. We availed this as an excellent opportunity to develop a system that identifies trash using a deep convolutional neural network (CNN). This paper proposes a real-time garbage identification system based on a deep CNN architecture with eight distinct classes for the training dataset. After identifying the garbage, the CCTV camera captures a video of the individual placing the trash in the incorrect location and sends an alert notice to the relevant authority.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.27 no.2
• /
• pp.167-176
• /
• 2024

Lip-reading is the task of inferring the speaker's utterance from silent video based on learning of lip movements. It is very challenging due to the inherent ambiguities present in the lip movement such as different characters that produce the same lip appearances. Recent advances in deep learning models such as Transformer and Temporal Convolutional Network have led to improve the performance of lip-reading. However, most previous works deal with English lip-reading which has limitations in directly applying to Korean lip-reading, and moreover, there is no a large scale Korean lip-reading dataset. In this paper, we introduce the first large-scale Korean lip-reading dataset with more than 120 k utterances collected from TV broadcasts containing news, documentary and drama. We also present a preprocessing method which uniformly extracts a facial region of interest and propose a transformer-based model based on grapheme unit for sentence-level Korean lip-reading. We demonstrate that our dataset and model are appropriate for Korean lip-reading through statistics of the dataset and experimental results.

• International Journal of Advanced Culture Technology
• /
• v.12 no.1
• /
• pp.1-10
• /
• 2024

While technologies such as the 4th revolution and artificial intelligence (AI), which create new value through the convergence of intelligent information technology, are becoming hot topics, the beauty industry is rapidly developing and combining information and communication technology to produce beauty items based on smartphones among mobile technologies. As the area of expands, YouTube is forming a network through various means of information. In particular, beauty-related YouTube videos are a field of great interest and popularity among the public. By classifying the makeup characteristics according to the emotional images shown in domestic YouTube videos by emotional image and identifying the characteristics of makeup, the needs for watching YouTube makeup videos are identified. We aim to build trust in the delivery of information about makeup. The emotional images were divided into four types: 'modern', 'natural', 'gorgeous', and cute. Among the domestic makeup YouTubers, Pony, Isabe and Shinnim, Lamuque were selected. By organizing more diverse makeup-related content systematically and creatively, we expect to have a positive influence on k-makeup not only domestically but also overseas. We aim to provide basic data for follow-up research on makeup YouTuber videos in the field of cosmetology and contribute to marketing plans for the development of the beauty content industry and establishment of promotional strategies.

• Journal of the Korean Society of Safety
• /
• v.35 no.5
• /
• pp.74-85
• /
• 2020

Smart phone zombie or Smombie means pedestrians who walk without attention to their surroundings because they are focused upon their smart phone. Because the traffic accidents and injuries caused by Smombie have been increased rapidly in recent years, the social attention and policies are needed to prevent it. This study was conducted to analyze Smombie's current status and some solutions used before and to propose new improved method through the latest ICT trend. In this study, we did the field survey to check Smombies at several places in Seoul through people counting, and found that a lot of pedestrians still use the smart phone while walking. And we analyzed many case studies about some solutions to prevent Smombies previously. The case studies include legal regulations, government policies, smart phone app services and facilities that are used before. We studied them through internet searches and reference studies and we also checked the current operating situation as visiting several places that the solutions actually has been operated. Therefore, we found there are some limitations in previous solutions in terms of effectiveness and management. To consider new solution that can be expected to overcome the limitations, we analyzed the latest ICT trends focused on features to utilize the Smombie prevention, especially video recognition and digital signage. In these days, video recognition has been developed rapidly with assistance of AI technology and it can recognize the specific pedestrian's characteristics such as holding smart phone as well as hair style, clothes, backpack and etc. On the other hands, the digital signage is the convergence device that includes big display, network connection and various IoT sensors. It can be used as public media in many places for public services as well as advertising. Through these analysis results, we show the requirements and the user scenario for the improved method to prevent Smombie. Finally, we propose to develop R&D technology to recognize Smombie exactly as pedestrian attributes and to spread creative contents to increase pedestrian's interest and engagement for Smombie prevention through digital signage.

• International conference on construction engineering and project management
• /
• 2022.06a
• /
• pp.1243-1244
• /
• 2022

In recent years, the growing interest in off-site construction has led to factories scaling up their manufacturing and production processes in the construction sector. Consequently, continuous large-scale site monitoring in low-variability environments, such as prefabricated components production plants (precast concrete production), has gained increasing importance. Although many studies on computer vision-based site monitoring have been conducted, challenges for deploying this technology for large-scale field applications still remain. One of the issues is collecting and transmitting vast amounts of video data. Continuous site monitoring systems are based on real-time video data collection and analysis, which requires excessive computational resources and network traffic. In addition, it is difficult to integrate various object information with different sizes and scales into a single scene. Various sizes and types of objects (e.g., workers, heavy equipment, and materials) exist in a plant production environment, and these objects should be detected simultaneously for effective site monitoring. However, with the existing object detection algorithms, it is difficult to simultaneously detect objects with significant differences in size because collecting and training massive amounts of object image data with various scales is necessary. This study thus developed a large-scale site monitoring system using edge computing and a small-object detection system to solve these problems. Edge computing is a distributed information technology architecture wherein the image or video data is processed near the originating source, not on a centralized server or cloud. By inferring information from the AI computing module equipped with CCTVs and communicating only the processed information with the server, it is possible to reduce excessive network traffic. Small-object detection is an innovative method to detect different-sized objects by cropping the raw image and setting the appropriate number of rows and columns for image splitting based on the target object size. This enables the detection of small objects from cropped and magnified images. The detected small objects can then be expressed in the original image. In the inference process, this study used the YOLO-v5 algorithm, known for its fast processing speed and widely used for real-time object detection. This method could effectively detect large and even small objects that were difficult to detect with the existing object detection algorithms. When the large-scale site monitoring system was tested, it performed well in detecting small objects, such as workers in a large-scale view of construction sites, which were inaccurately detected by the existing algorithms. Our next goal is to incorporate various safety monitoring and risk analysis algorithms into this system, such as collision risk estimation, based on the time-to-collision concept, enabling the optimization of safety routes by accumulating workers' paths and inferring the risky areas based on workers' trajectory patterns. Through such developments, this continuous large-scale site monitoring system can guide a construction plant's safety management system more effectively.

• Proceedings of the Korea Multimedia Society Conference
• /
• 2000.11a
• /
• pp.66-69
• /
• 2000

웹이 등장하면서 지금까지 인터넷 상에서 텍스트와 이미지를 이용하여 정보를 표현하고 전달하는 방법이 가장 많이 사용되어왔다. 그러나 웹 관련 기술의 비약적인 발달과 네트워크 속도의 증가 및 인터넷의 급속한 보급으로 단순한 텍스트와 이미지 중심의 HTML 문서를 이용한 정보의 전달이 아닌 멀티미디어 데이터를 이용한 정보의 표현과 전달이 점차 증대되고 있다. 이에 따라 멀티미디어 데이터를 전송하기 위한 스트리밍 프로토콜도 등장하였다. 최근에는 컴퓨터의 성능 증가 및 네트워크 속도의 증가(초고속 통신 서비스의 보급)에 의해 멀티미디어 데이터의 전송이 가능하게 됨으로써 기존의 공중파나 CATV 방송국의 형태 지니고 인터넷 상에서 실시간 생방송 서비스와 VOD(Video On Demand) 서비스를 제공하는 인터넷 방송국이 급속하게 생겨나고 있다. (11) 인터넷 방송은 동영상과 오디오의 실시간 전달을 가능하게 하는 멀티미디어 스트리밍 기술과 멀티미디어를 실시 간으로 전송할 수 있는 실시간 전송 프로토콜을 기반으로 발전하고 있다. 인터넷 상에서 멀티미디어 스트리밍 서비스를 하는 대부분의 인터넷 방송은 스트리밍 서버로서 RealNetworks사의 RealSystem과 Microsoft사의 WMT(Windows Media Technologies)를 사용하고 있다. 본 논문은 Real Server와 WMT의 비교 분석을 통해 실시간 전송 프로토콜을 지원하고, 멀티미디어 스트리밍 기술을 지원하는 자바를 기반으로 한 분산 서버 구조의 스트리밍 서버, 서버간의 부하를 제어하는 미들웨어, 멀티미디어 스트림을 재생할 수 있는 클라이언트를 설계하고 구현한다.있다.구현한다. 이렇게 구현된 시스템은 전자 상거래, 가상 쇼핑몰, 가상 전시화, 또는 3차원 게임이나 가상교육 시스템과 같은 웹기반 응용프로그램에 사용될 수 있다.물을 보존·관리하는 것이 필요하다. 이는 도서관의 기능만으로는 감당하기 어렵기 때문에 대학정보화의 센터로서의 도서관과 공공기록물 전문 담당자로서의 대학아카이브즈가 함께 하여 대학의 공식적인 직무 관련 업무를 원활하게 지원하고, 그럼으로써 양 기관의 위상을 높이는 상승효과를 낼 수 있다.하여는, 인쇄된 일차적 정보자료의 검색방법등을 개선하고, 나아가서는 법령과 판례정보를 위한 효율적인 시스템을 구축하며, 뿐만 아니라 이용자의 요구에 충분히 대처할 수 잇는 도서관으로 변화되는 것이다. 이와 함께 가장 중요한 것은 법과대학과 사법연수원에서 법학 연구방법에 관한 강좌를 개설하여 각종 법률정보원의 활용 내지 도서관 이용방법에 관하여 교육하는 것이다.글을 연구하고, 그 결과에 의존하여서 우리의 실제의 생활에 사용하는 $\boxDr$한국어사전$\boxUl$등을 만드는 과정에서, 어떤 의미에서 실험되었다고 말할 수가 있는 언어과학의 연구의 결과에 의존하여서 수행되는 철학적인 작업이다. 여기에서는 하나의 철학적인 연구의 시작으로 받아들여지는 이 의미분석의 문제를 반성하여 본다. 것이 필요하다고 사료된다.크기에 의존하며, 또한 이러한 영향은 $(Ti_{1-x}AI_{x})N$ 피막에 존재하는 AI의 함량이 높고, 초기에 증착된 막의 업자 크기가 작을 수록 클 것으로 여겨진다. 그리고 환경의 의미의 차이에 따라 경관의 미학적 평가가 달라진 것으로

• Journal of Cadastre & Land InformatiX
• /
• v.51 no.1
• /
• pp.53-65
• /
• 2021

C-ITS(Cooperative Intelligent Transport System) that pursues traffic safety and convenience uses various sensors to generate traffic information. Therefore, it is necessary to improve the sensor-related technology to increase the efficiency and reliability of the traffic information. Recently, the role of CCTV in collecting video information has become more important due to advances in AI(Artificial Intelligence) technology. In this study, we propose to identify and track dynamic objects(vehicles, people, etc.) in CCTV images, and to analyze and provide information about them in various environments. To this end, we conducted identification and tracking of dynamic objects using the Yolov4 and Deepsort algorithms, establishment of real-time multi-user support servers based on Kafka, defining transformation matrices between images and spatial coordinate systems, and map-based dynamic object visualization. In addition, a positional consistency evaluation was performed to confirm its usefulness. Through the proposed scheme, we confirmed that CCTVs can serve as important sensors to provide relevant information by analyzing road conditions in real time in terms of road infrastructure beyond a simple monitoring role.

• Journal of The Korean Association of Information Education
• /
• v.24 no.5
• /
• pp.473-481
• /
• 2020

Data science starts with small data analysis and includes machine learning and deep learning for big data analysis. Data science is a core area of artificial intelligence technology and should be systematically reflected in the school curriculum. For data science education, The Entry also provides a data analysis tool for elementary education. In a big data analysis, data samples are extracted and analysis results are interpreted through statistical guesses and judgments. In this paper, the big data analysis area that requires statistical knowledge is excluded from the elementary area, and data science education examples focusing on the elementary area are proposed. To this end, the general data science education stage was explained first, and the elementary data science education stage was newly proposed. After that, an example of comparing values of data variables and an example of analyzing correlations between data variables were proposed with public small data provided by Entry, according to the elementary data science education stage. By using these Entry data-analysis examples proposed in this paper, it is possible to provide data science convergence education in elementary school, with given data generated from various subjects. In addition, data science educational materials combined with text, audio and video recognition AI tools can be developed by using the Entry.

• Journal of the Korean BIBLIA Society for library and Information Science
• /
• v.32 no.4
• /
• pp.5-24
• /
• 2021

The purpose of this study was to investigate and analyze the operating conditions of lecture contents in contactless online classes for University students. First, as a result of analyzing the responses of 93 respondents, 93.3% of the respondents took real-time online lectures (47.7%) or recorded video lectures (45.6%). Second, as a result of analyzing the contents used as textbooks, it was found that e-books (materials) and paper books (materials) were used together (36.6%), or e-books or electronic materials (36.6% and 37.6% respectively) were used in both liberal arts (47.3%) and major subjects (39.8%). In addition to textbooks, both major subjects and liberal arts highly used web materials (47.6% and 40.5% respectively) and YouTube materials (33.3% and 48.0% respectively) as external materials. Third, both liberal arts and major subjects used 'electronic files in the form of PPT or text organized and written by instructors' (62.9% and 58.1% respectively), 'internet materials' (16.7% and 19% respectively) and 'paper book or materials' (10.4% and 12.3% respectively) to share lecture contents. For the screen displayed lecture contents, 93.5% of the respondents satisfied in major subjects, and 90.2% of the respondents satisfied in liberal arts. These results suggest developing multimedia-based lecture contents and an evaluation solution capable of real-time exam supervision, developing a task management system capable of AI-based plagiarism search, task guidance, and task evaluation, and institutionalizing a solution to copyright problems for electronicizing lecture materials so that lectures can be given in the ubiquitous environment.