• Journal of the Korean Society of Radiology
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• v.16 no.1
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• pp.25-34
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• 2022

Brain computed tomography (CT) is useful for brain lesion diagnosis, such as brain hemorrhage, due to non-invasive methodology, 3-dimensional image provision, low radiation dose. However, there has been numerous misdiagnosis owing to a lack of radiologist and heavy workload. Recently, object detection technologies based on artificial intelligence have been developed in order to overcome the limitations of traditional diagnosis. In this study, the applicability of a deep learning-based YOLOv5s model was evaluated for brain hemorrhage detection using brain CT images. Also, the effect of hyperparameters in the trained YOLOv5s model was analyzed. The YOLOv5s model consisted of backbone, neck and output modules. The trained model was able to detect a region of brain hemorrhage and provide the information of the region. The YOLOv5s model was trained with various activation functions, optimizer functions, loss functions and epochs, and the performance of the trained model was evaluated in terms of brain hemorrhage detection accuracy and training time. The results showed that the trained YOLOv5s model is able to provide a bounding box for a region of brain hemorrhage and the accuracy of the corresponding box. The performance of the YOLOv5s model was improved by using the mish activation function, the stochastic gradient descent (SGD) optimizer function and the completed intersection over union (CIoU) loss function. Also, the accuracy and training time of the YOLOv5s model increased with the number of epochs. Therefore, the YOLOv5s model is suitable for brain hemorrhage detection using brain CT images, and the performance of the model can be maximized by using appropriate hyperparameters.

• Journal of the Korea Society for Simulation
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• v.32 no.3
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• pp.43-53
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• 2023

In this detailed and comprehensive study, our primary focus has been placed on accurately gauging the number of visitors and their real-time locations in commercial spaces. Particularly, in a real cafe, using security cameras, we have developed a system that can offer live updates on available seating and predict future congestion levels. By employing YOLO, a real-time object detection and tracking algorithm, the number of visitors and their respective locations in real-time are also monitored. This information is then used to update a cafe's indoor map, thereby enabling users to easily identify available seating. Moreover, we developed a model that predicts the congestion of a cafe in real time. The sophisticated model, designed to learn visitor count and movement patterns over diverse time intervals, is based on Long Short Term Memory (LSTM) to address the vanishing gradient problem and Sequence-to-Sequence (Seq2Seq) for processing data with temporal relationships. This innovative system has the potential to significantly improve cafe management efficiency and customer satisfaction by delivering reliable predictions of cafe congestion to all users. Our groundbreaking research not only demonstrates the effectiveness and utility of indoor location tracking technology implemented through security cameras but also proposes potential applications in other commercial spaces.

• Journal of Korea Entertainment Industry Association
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• v.13 no.4
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• pp.131-138
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• 2019

The film enters the color film from black and white, and the screen image changes qualitatively. The color in the film not only has the reproduction function of the restoration object like the objective appearance, but also has the function of conveying different subjective emotions. It can express the color and can't express it. The artistic effect conveys the information content that the story itself can't convey, so the color of the film becomes an important part of the film language. The color in the film is presented on the screen in the form of single-screen color, scene color, full-color color tone, and various color chains designed according to different contradictions and conflicts. Because the film art and art means are assembled by montage, he colors in the picture also form a montage form. People call it "color montage". People's subjective nature of color criticism and acceptance of color language also depend on various local tones. The accurate expression of the relationship, the unique attribute of color determines that the color must enter the structural state in order to express its unique charm. The color of the film only has the real aesthetic value when it enters the level of "color structure". This paper studies the color of Chinese and Western films from the differences between the color thinking of Chinese and Western film directors and the cultural implication of Chinese and Western film colors. The western film director emphasizes the structure of color and pays attention to the use of tonal montage to convey the characters. Emotions reflect the characteristics of a subjective color. Beginning with the "fifth-generation" director of Chinese film, the new journey of film color language has been opened. In the process of blending love and scenery, the film style of "image-in-one" has been achieved.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.1
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• pp.44-51
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• 2023

The Convention on the International Regulations for Preventing Collisions at Sea, 1972 (COLREGs) was adopted to prevent ships from colliding with other ships or any object such as the seabed. COLREGs have been codified and refined since the mid-19th century, and have reached the present. Therefore, the terms and sentences used in COLREGs also have distinct academic and legal connotations. However, in the Maritime Safety Act of the Republic of Korea, which translated COLREGs into domestic law, the "risk of collision" and the "danger of collision" was used in the law without distinguishing their meanings. Accordingly, the difference between "risk" and "danger" was analyzed with reference to the definition of risk by an authoritative international organization of the United Nations such as the International Maritime Organization and the International Organization for Standardization as a well-known and authoritative non governmental organization. In addition, the cases codified in COLREGs and translated cases in the Maritime Safety Act were analyzed to highlight the need for amending the Maritime Safety Act. From the perspective of safe navigation, it is expected that the Maritime Safety Act in the future would distinguish between "danger" and "risk" so that the efforts of watch officers to prevent collisions could be further systematized.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.5
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• pp.217-228
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• 2023

Video instance segmentation is an intelligent visual task with high complexity because it not only requires object instance segmentation for each image frame constituting a video, but also requires accurate tracking of instances throughout the frame sequence of the video. In special, human instance segmentation in drama videos has an unique characteristic that requires accurate tracking of several main characters interacting in various places and times. Also, it is also characterized by a kind of the class imbalance problem because there is a significant difference between the frequency of main characters and that of supporting or auxiliary characters in drama videos. In this paper, we introduce a new human instance datatset called MHIS, which is built upon drama videos, Miseang, and then propose a novel video data augmentation method, CDVA, in order to overcome the data imbalance problem between character classes. Different from the previous video data augmentation methods, the proposed CDVA generates more realistic augmented videos by deciding the optimal location within the background clip for a target human instance to be inserted with taking rich spatio-temporal context embedded in videos into account. Therefore, the proposed augmentation method, CDVA, can improve the performance of a deep neural network model for video instance segmentation. Conducting both quantitative and qualitative experiments using the MHIS dataset, we prove the usefulness and effectiveness of the proposed video data augmentation method.

• International Journal of Computer Science & Network Security
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• v.22 no.1
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• pp.340-346
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• 2022

The article examines the formation of the scientific paradigm of transformation of the potential-forming space of the regional economy under the influence of intellectual and innovative determinants. Based on the study of different scientific views on the nature and properties of potential-forming space through the study of approaches to understanding the concept of "space" clarified the complexity and multifaceted nature of the phenomenon and found that its characteristics are relevant to the industrial development model. It is revealed that the leading modern trends related to the spread of globalization and regionalization, rapid development of information and communication technologies, diffusion of innovations accompany the transition from industrial to post-industrial development and its development, which leads to new development: changes production, nature and relations between business entities, etc. It is proved that under such conditions, the region as a key element of the economic system, acquires a leading role in achieving sustainable and balanced development. These processes significantly affect the potential-forming space of the regional economy under the influence of intellectual and innovative determinants, leading to the need for its transformation and change in accordance with modern realities, which is reflected in thorough research on the formation of scientific paradigm based on the formation of its theoretical foundations and methodological basis. This study reveals the essence, role, functions, structure, process of formation of the scientific paradigm of transformation of the potential-forming space of the regional economy under the influence of intellectual and innovative determinants. It is proved that the formation of the modern scientific paradigm of transformation of the potential-forming space of the regional economy under the influence of intellectual and innovative determinants occurs in the context of building a post-industrial model of development, accompanied by consideration of the region as a spatial object territories from the physical plane to the spatial environment in which the development of human capital, innovation and self-development of the region. Taking into account the above, the article outlines the prerequisites and factors of formation of the scientific paradigm of transformation of the potential-forming space of the regional economy under the influence of intellectual and innovative determinants.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6D
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• pp.1025-1032
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• 2006

Sensor modeling of high-resolution satellites is a prerequisite procedure for mapping and GIS applications. Sensor models, describing the geometric relationship between scene and object, are divided into two main categories, which are rigorous and approximate sensor models. A rigorous model is based on the actual geometry of the image formation process, involving internal and external characteristics of the implemented sensor. However, approximate models require neither a comprehensive understanding of imaging geometry nor the internal and external characteristics of the imaging sensor, which has gathered a great interest within photogrammetric communities. This paper described a comparison between rigorous and various approximate sensor models that have been used to determine three-dimensional positions, and proposed the appropriate sensor model in terms of the satellite imagery usage. Through the case study of using IKONOS satellite scenes, rigorous and approximate sensor models have been compared and evaluated for the positional accuracy in terms of acquirable number of ground controls. Bias compensated RFM(Rational Function Model) turned out to be the best among compared approximate sensor models, both modified parallel projection and parallel-perspective model were able to be modelled with a small number of controls. Also affine transformation, one of the approximate sensor models, can be used to determine the planimetric position of high-resolution satellites and perform image registration between scenes.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.58.1-59
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• 2021

Exploration of asteroids' internal structure is essential for understanding their evolutional history. It also provides a fundamental information about the history of coalescence and collision of the solar system. Among several models of the internal structures, the rubble-pile model, confirmed by the near-Earth asteroid (25143) Itokawa by Hayabusa mission [1], is now widely regarded as the most common to asteroids with size ranging from 200 m to 10 km [2]. On the contrary, monolithic and core-mantle structures are also possible for small asteroids [3]. It is, however, still challenging to look through the interior of a target object using remote-sensing devices. In this presentation, we introduce our ongoing research conducted at Seoul National and propose an idea to infer the internal structure of Apophis using available instruments. Itokawa's research provides an important benchmark for Apophis exploration because both asteroids have similar size and composition [4][5]. We have conducted research on Itokawa's evolution in terms of collision and space weathering. Space weathering is the surface alteration process caused by solar wind implantation and micrometeorite bombardment [6]. Meanwhile, resurfacing via a collision acts as a counter-process of space weathering by exposing fresh materials under the matured layer and lower the overall degree of space weathering. Therefore, the balance of these two processes determine the space weathering degrees of the asteroid. We focus on the impact evidence on the boulder surface and found that space weathering progresses in only 100-10,000 years and modifies the surface optical properties (Jin & Ishiguro, KAS 2020 Fall Meeting). It is important to note that the timescale is significantly shorter than the Itokawa's age, suggesting that the asteroid can be totally processed by space weathering. Accordingly, our result triggers a further discussion about why Itokawa indicates a moderately fresh spectrum (Sq-type denotes less matured than S-type). For example, Itokawa's smooth terrains show a weaker degree of space weathering than other S-type asteroids [7]. We conjecture that the global seismic shaking caused by collisions with >1 mm-sized interplanetary dust particles induces granular convection, which hinders the progression of space weathering [8]. Note that the efficiency of seismic wave propagation is strongly dependent on the internal structure of the asteroid. Finally, we consider possible approaches to investigate Apophis's internal structure. The first idea is studying the space weathering age, as conducted for Itokawa. If Apophis indicates a younger age, the internal structure would have more voids [9]. In addition, the 2029 close encounter with Earth provides a rare natural opportunity to witness the contrast between before and after the event. If the asteroid exhibits a slight change in shape and space weathering degree, one can determine the physical structure of the internal materials (e.g., rubble-pile monolithic, thick or thin regolith layer, the cohesion of the materials). We will also consider a possible science using a seismometer.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.73-80
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• 2023

The recent steep increase in the minimum hourly wage has increased the burden of labor costs, and the share of unmanned stores is increasing in the aftermath of COVID-19. As a result, theft crimes targeting unmanned stores are also increasing, and the "Just Walk Out" system is introduced to prevent such thefts, and LiDAR sensors, weight sensors, etc. are used or manually checked through continuous CCTV monitoring. However, the more expensive sensors are used, the higher the initial cost of operating the store and the higher the cost in many ways, and CCTV verification is difficult for managers to monitor around the clock and is limited in use. In this paper, we would like to propose an AI image processing fusion algorithm that can solve these sensors or human-dependent parts and detect customers who perform abnormal behaviors such as theft at low costs that can be used in unmanned stores and provide cloud-based notifications. In addition, this paper verifies the accuracy of each algorithm based on behavior pattern data collected from unmanned stores through motion capture using mediapipe, object detection using YOLO, and fusion algorithm and proves the performance of the convergence algorithm through various scenario designs.

• Korean Journal of Remote Sensing
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• v.39 no.6_3
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• pp.1679-1692
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• 2023

South Korea is a country that emits a large amount of pollutants as a result of population growth and industrial development and is also severely affected by transboundary air pollution due to its geographical location. As pollutants from both domestic and foreign sources contribute to air pollution in Korea, the location of air pollutant emission sources is crucial for understanding the movement and distribution of pollutants in the atmosphere and establishing national-level air pollution management and response strategies. Based on this background, this study aims to effectively acquire spatial information on domestic and international air pollutant emission sources, which is essential for analyzing air pollution status, by utilizing high-resolution optical satellite images and deep learning-based image segmentation models. In particular, industrial parks and quarries, which have been evaluated as contributing significantly to transboundary air pollution, were selected as the main research subjects, and images of these areas from multi-purpose satellites 3 and 3A were collected, preprocessed, and converted into input and label data for model training. As a result of training the U-Net model using this data, the overall accuracy of 0.8484 and mean Intersection over Union (mIoU) of 0.6490 were achieved, and the predicted maps showed significant results in extracting object boundaries more accurately than the label data created by course annotations.