• 한국IT서비스학회:학술대회논문집
• /
• 2008.05a
• /
• pp.79-84
• /
• 2008

전세계 국가는 21세기 메가 트렌드인 기술 융합(Technology Convergence) 추세에 발 맞춰 미래비전 및 전략수립에 몰두하고 있다. 그리고, 공통적으로 정보통신(IT)기술 및 서비스를 기반으로 한 자국의 국부 증대와 신산업 창출을 시나리오 기법을 활용하여 이야기 하고 있다. 하지만 국내의 경우 비전연구 및 전략수립에 대한 연구가 초보단계로 기존의 IT 단독 기술에 의한 연구개발 방법을 그대로 활용할 경우, 기술 융합 메가 트렌드 연구개발에 능동적으로 대처하기에는 미흡하다는 지적이다. 따라서, 본 논문에서는 시나리오 기법을 활용한 비전연구 사례를 분석하고, 향후 시나리오 비전연구 방향을 제시한다.

• Journal of Sensor Science and Technology
• /
• v.33 no.3
• /
• pp.185-185
• /
• 2024

• Journal of the Korea Convergence Society
• /
• v.12 no.10
• /
• pp.189-201
• /
• 2021

The art of dynamic images has experienced three development stages, including experimental films, recording art, and new media image. By introducing all kinds of new materials, new media to the art, and the art of dynamic images has created more freedom for art creation. With the development of digital information technology, dynamic image works have put forward an increasingly high requirement of visual art. The combination of dynamic images and visual illusion can give rise to different forms and expression methods, thus endowing artworks with more vigor. This paper provides an overview by sorting out the lineage and development of dynamic images in the background, as well as understanding the application and performance of contrasted visual illusion. Based on the understanding of the characteristics of visual illusion, we discuss the new characteristics of applying the theory of visual illusion to new media dynamic images in relation to the technical approach of dynamic images. Through the analysis of specific works of Telematic Vision, we search for its reasonable combination and find the appropriate technical means of implementation. We discuss how to use digital multimedia technology and spatial optical illusion to make the design more novel and impactful, and consider how the combination of digital dynamic image technology and visual illusion should be interpreted and applied.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.1
• /
• pp.166-179
• /
• 2021

Recently, with the development of technology, computer vision research based on the human visual system has been actively conducted. Saliency maps have been used to highlight areas that are visually interesting within the image, but they can suffer from low performance due to external factors, such as an indistinct background or light source. In this study, existing color, brightness, and contrast feature maps are subjected to multiple shape and orientation filters and then connected to a fully connected layer to determine pixel intensities within the image based on location-based weights. The proposed method demonstrates better performance in separating the background from the area of interest in terms of color and brightness in the presence of external elements and noise. Location-based weight normalization is also effective in removing pixels with high intensity that are outside of the image or in non-interest regions. Our proposed method also demonstrates that multi-filter normalization can be processed faster using parallel processing.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2017.11a
• /
• pp.139-141
• /
• 2017

화재는 다른 재난보다 확산 속도가 빠르기 때문에 신속하고 정확한 감지와 지속적인 감시가 요구된다. 최근, 신속하고 정확한 화재 감지를 위해, CCTV(Closed-Circuit TeleVision)으로 획득한 이미지를 기계학습(Machine Learning)을 이용해 화재 발생 여부를 감지하는 화재 감지 시스템이 주목받고 있다. 본 논문에서는 기계학습의 기술 중 정확도가 가장 높은 딥러닝(Deep Learning)기반의 CCTV 화재 감지 시스템을 제안한다. 본 논문의 시스템은 딥러닝 기술 적용뿐만이 아니라, CCTV 이미지 전처리 과정을 보완함으로써 딥러닝에서의 미지 데이터(unseen data)의 낮은 분류 정확도 문제인 과적합(overfitting)문제를 해결하였다. 본 논문의 시스템은 약 80,000 개의 CCTV 이미지 데이터를 학습하여, 90% 이상의 화재 이미지 분류 정확도의 성능을 보여주었다.

• Physical Therapy Korea
• /
• v.29 no.2
• /
• pp.87-93
• /
• 2022

To solve the pathological problems of the musculoskeletal system based on evidence, a sophisticated analysis of human motion is required. Traditional optical motion capture systems with high validity and reliability have been utilized in clinical practice for a long time. However, expensive equipment and professional technicians are required to construct optical motion capture systems, hence they are used at a limited capacity in clinical settings despite their advantages. The development of information technology has overcome the existing limit and paved the way for constructing a motion capture system that can be operated at a low cost. Recently, with the development of computer vision-based technology and optical markerless tracking technology, webcam-based 3D human motion analysis has become possible, in which the intuitive interface increases the user-friendliness to non-specialists. In addition, unlike conventional optical motion capture, with this approach, it is possible to analyze motions of multiple people at simultaneously. In a non-optical motion capture system, an inertial measurement unit is typically used, which is not significantly different from a conventional optical motion capture system in terms of its validity and reliability. With the development of markerless technology and advent of non-optical motion capture systems, it is a great advantage that human motion analysis is no longer limited to laboratories.

• Journal of the Korean Wood Science and Technology
• /
• v.50 no.6
• /
• pp.490-498
• /
• 2022

The current study aimed to verify the image segmentation ability of rays in tangential thin sections of conifers using artificial intelligence technology. The applied model was Mask region-based convolutional neural network (Mask R-CNN) and softwoods (viz. Picea jezoensis, Larix gmelinii, Abies nephrolepis, Abies koreana, Ginkgo biloba, Taxus cuspidata, Cryptomeria japonica, Cedrus deodara, Pinus koraiensis) were selected for the study. To take digital pictures, thin sections of thickness 10-15 ㎛ were cut using a microtome, and then stained using a 1:1 mixture of 0.5% astra blue and 1% safranin. In the digital images, rays were selected as detection objects, and Computer Vision Annotation Tool was used to annotate the rays in the training images taken from the tangential sections of the woods. The performance of the Mask R-CNN applied to select rays was as high as 0.837 mean average precision and saving the time more than half of that required for Ground Truth. During the image analysis process, however, division of the rays into two or more rays occurred. This caused some errors in the measurement of the ray height. To improve the image processing algorithms, further work on combining the fragments of a ray into one ray segment, and increasing the precision of the boundary between rays and the neighboring tissues is required.

• Journal of Information Technology Services
• /
• v.21 no.6
• /
• pp.21-37
• /
• 2022

Due to the development of technology and medical care following the 4th industrial revolution, the medical paradigm is shifting towards patient-centered medical services. Based on the development of smart home technology, the residential environment is changing into a residential space that cares for and heals the lifestyles and the healthcare of families. As lifestyle changes, the concept of supporting smart home care based on the residential environment is making it possible to build a smart home IoT service design with enhanced accessibility and convenience for medical appointments and well-being lifestyle care. This paper is a study on user-centered health care smart home IoT service design suitable for family members based on the health care, beauty care, exercise care, and customized diet care beyond the conventional concept of health care monitoring. Based on the analysis, this paper proposes a personal care coordinate smart home service design in a human-centered wellness clinic care smart home service design environment. Human-centered wellness clinic smart home IoT service design is meaningful in presenting a vision for research on smart home service design that links hospital-linked and care-linked service industries, which should be considered from the smart home construction planning stage.

• Journal of KIBIM
• /
• v.13 no.3
• /
• pp.12-20
• /
• 2023

Deep learning-based anomaly detection technology is used in various fields such as computer vision, speech recognition, and natural language processing. In particular, this technology is applied in various fields such as monitoring manufacturing equipment abnormalities, detecting financial fraud, detecting network hacking, and detecting anomalies in medical images. However, in the field of construction and architecture, research on deep learning-based data anomaly detection technology is difficult due to the lack of digitization of domain knowledge due to late digital conversion, lack of learning data, and difficulties in collecting and processing field data in real time. This study acquires necessary data through IoT (Internet of Things) from the viewpoint of monitoring for environmental management of architectural spaces, converts them into a database, learns deep learning, and then supports anomaly patterns using AI (Artificial Infelligence) deep learning-based anomaly detection. We propose an implementation process. The results of this study suggest an effective environmental anomaly pattern detection solution architecture for environmental management of architectural spaces, proving its feasibility. The proposed method enables quick response through real-time data processing and analysis collected from IoT. In order to confirm the effectiveness of the proposed method, performance analysis is performed through prototype implementation to derive the results.

• International Journal of Concrete Structures and Materials
• /
• v.4 no.1
• /
• pp.37-43
• /
• 2010

Theoretical models based on modern interpretations of the morphology and interactions of cement hydration products are developed for prediction of the mechanical properties of hydrated cement paste (hcp). The models are based on the emerging nanostructural vision of calcium silicate hydrate (C-S-H) morphology, and account for the intermolecular interactions between nano-scale calcium C-S-H particles. The models also incorporate the effects of capillary porosity and microcracking within hydrated cement paste. The intrinsic modulus of elasticity and tensile strength of hydrated cement paste are determined based on intermolecular interactions between C-S-H nano-particles. Modeling of fracture toughness indicates that frictional pull-out of the micro-scale calcium hydroxide (CH) platelets makes major contributions to the fracture energy of hcp. A tensile strength model was developed for hcp based on the linear elastic fracture mechanics theories. The predicted theoretical models are in reasonable agreements with empirical models developed based on the experimental performance of hcp.