• Journal of Digital Convergence
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• v.17 no.3
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• pp.55-61
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• 2019

Multimedia materials were developed to creative children's songs to elementary schoolers so as to improve favorable personality. To this end, we selected elementary school students to select appropriate songs for the cultivation of humanity, and produced multimedia including various image materials such as animation, documentary, chorus, dance performances, and interviews. Above all, we have created a teaching - learning process and presented the program so that teachers can easily guide students to agitation. As a result, the change of personality of elementary school students was positively shown through sway broadcasting, and I tried to give practical examples of practical application for cultivation of creativity and personality that should be emphasized at elementary school.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.4
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• pp.116-128
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• 2011

In this paper, we propose the structure of a high-performance face-detection engine that responds well to facial rotating changes using rotation transformation which minimize the required memory usage compared to the previous face-detection engine. The validity of the proposed structure has been verified through the implementation of FPGA. For high performance face detection, the MCT (Modified Census Transform) method, which is robust against lighting change, was used. The Adaboost learning algorithm was used for creating optimized learning data. And the rotation transformation method was added to maintain effectiveness against face rotating changes. The proposed hardware structure was composed of Color Space Converter, Noise Filter, Memory Controller Interface, Image Rotator, Image Scaler, MCT(Modified Census Transform), Candidate Detector / Confidence Mapper, Position Resizer, Data Grouper, Overlay Processor / Color Overlay Processor. The face detection engine was tested using a Virtex5 LX330 FPGA board, a QVGA grade CMOS camera, and an LCD Display. It was verified that the engine demonstrated excellent performance in diverse real life environments and in a face detection standard database. As a result, a high performance real time face detection engine that can conduct real time processing at speeds of at least 60 frames per second, which is effective against lighting changes and face rotating changes and can detect 32 faces in diverse sizes simultaneously, was developed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.7-15
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• 2022

Since the direct and indirect damage caused by the fire in the underground utility tunnel will cause great damage to society as a whole, it is necessary to make efforts to prevent and control it in advance. The most of the fires that occur in cables are caused by short circuits, earth leakage, ignition due to over-current, overheating of conductor connections, and ignition due to sparks caused by breakdown of insulators. In order to find the cause of fire at an early stage due to the characteristics of the underground utility tunnel and to prevent disasters and safety accidents, we are constantly managing it with a detection system using image analysis and making efforts. Among them, a case of developing a fire detection system using CCTV-based deep learning image analysis technology has been reported. However, CCTV needs to be supplemented because there are blind spots. Therefore, we would like to develop a high-performance acoustic-based deep learning model that can prevent fire by detecting the spark sound before spark occurs. In this study, we propose a method that can collect sound in underground utility tunnel environments using microphone sensor through development and experiment of prototype module. After arranging an acoustic sensor in the underground utility tunnel with a lot of condensation, it verifies whether data can be collected in real time without malfunction.

• Korean Journal of Remote Sensing
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• v.36 no.6_2
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• pp.1579-1590
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• 2020

In this paper, spatially-adaptive denormalization (SPADE) based U-Net is proposed to detect changes by using high-resolution satellite images. The proposed network is to preserve spatial information using SPADE. Change detection methods using high-resolution satellite images can be used to resolve various urban problems such as city planning and forecasting. For using pixel-based change detection, which is a conventional method such as Iteratively Reweighted-Multivariate Alteration Detection (IR-MAD), unchanged areas will be detected as changing areas because changes in pixels are sensitive to the state of the environment such as seasonal changes between images. Therefore, in this paper, to precisely detect the changes of the objects that consist of the city in time-series satellite images, the semantic spatial objects that consist of the city are defined, extracted through deep learning based image segmentation, and then analyzed the changes between areas to carry out change detection. The semantic objects for analyzing changes were defined as six classes: building, road, farmland, vinyl house, forest area, and waterside area. Each network model learned with KOMPSAT-3A satellite images performs a change detection for the time-series KOMPSAT-3 satellite images. For objective assessments for change detection, we use F1-score, kappa. We found that the proposed method gives a better performance compared to U-Net and UNet++ by achieving an average F1-score of 0.77, kappa of 77.29.

• Journal of The Korean Association For Science Education
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• v.34 no.5
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• pp.469-478
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• 2014

To provide students an alternative image of science and scientist, we developed five lesson plans that include scientists' joy, anger, sorrow, and pleasure in their life. Through the 10 hour lessons with the five topics, we investigated the effect of our program on students' image change toward scientists, their science learning, and their career development in science field. Twenty high school students participated in our program and five of them were analyzed. The qualitative data included opinionnaire survey before and after the program, field note, video recording, students' worksheets, and interview. The science episode lessons that reflect the human side of scientists were designed in five steps. The first step is the one about imaging of scientists, the second step is the one about reading scientists' episode in their life, the third step is the one about investigating human side of scientists, the fourth step is the one about feeling sympathy in scientists' context, and the last step is the one about judging human side of scientists. Students participated in this program got to feel familiarity in scientists as well as confidence in science. By obtaining the alternative image of scientists after the class, it is expected that students will play roles of well-prepared supporters with scientific literacy.

• Journal of Internet Computing and Services
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• v.20 no.5
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• pp.105-111
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• 2019

Core technologies that lead the Fourth Industrial Revolution era, such as artificial intelligence, big data, and autonomous driving, are implemented and serviced through the rapid development of computing power and hyper-connected networks based on the Internet of Things. In this paper, we implement two different models for drivable area segmentation in various environment, and propose a better model by comparing the results. The models for drivable area segmentation are using DeepLab V3+ and Mask R-CNN, which have great performances in the field of image segmentation and are used in many studies in autonomous driving technology. For driving information in various environment, we use BDD dataset which provides driving videos and images in various weather conditions and day&night time. The result of two different models shows that Mask R-CNN has higher performance with 68.33% IoU than DeepLab V3+ with 48.97% IoU. In addition, the result of visual inspection of drivable area segmentation on driving image, the accuracy of Mask R-CNN is 83% and DeepLab V3+ is 69%. It indicates Mask R-CNN is more efficient than DeepLab V3+ in drivable area segmentation.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.4
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• pp.194-199
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• 2022

Preprocessing for high-quality data is required for high accuracy and usability in various and complex image data-based industries. However, when a contaminated hostile example that combines noise with existing image or video data is introduced, which can pose a great risk to the company, it is necessary to restore the previous damage to ensure the company's reliability, security, and complete results. As a countermeasure for this, restoration was previously performed using Defense-GAN, but there were disadvantages such as long learning time and low quality of the restoration. In order to improve this, this paper proposes a method using adversarial examples created through FGSM according to image segmentation in addition to using the VQ-VAE model. First, the generated examples are classified as a general classifier. Next, the unsegmented data is put into the pre-trained VQ-VAE model, restored, and then classified with a classifier. Finally, the data divided into quadrants is put into the 4-split-VQ-VAE model, the reconstructed fragments are combined, and then put into the classifier. Finally, after comparing the restored results and accuracy, the performance is analyzed according to the order of combining the two models according to whether or not they are split.

• Journal of Science of Art and Design
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• v.2
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• pp.161-192
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• 2000

Body has been high-lightened as one of the most important theme since the philosophy and the arts are focused on it in the late 20th century. It would be of worth to study the characteristics of contemporary fiber-art works, especially done by Abakanowiz who has been regarded as a dominant pioneer in the contemporary fiber-arts from the viewpoint of inter-grade of the physicals and the mental. This paper, therefore, deals with the Abaknowiz' works in the context of human body and body-signs. Life and works might be classified into 5 stages: first, learning period since her birth in 1930, second, creation period of Abakans, third, remodelling period of Abakans, fourth, composition and dissolution period of Abakans and the last and fifth, new transformation period of Abakans. 'Abakans' through her whole life as an artist have been a plastic language and based ultimately on external human body but in various materials and forms. Abakan as a human-sign uses the past experiences and the texts of the other world in mixed and overlapped forms. Life-size Abakans by Abaknowiz can be easily understood as Abakanowiz herself and her Polish ancestor at the same time. The neuter Abakans with mashed face and obscure body is a expressive figure of coexisting world with opposite concepts like war and ideology, anxiety and freedom, man and woman, and etc. Human body as body-sign is an extensive image has existed since our forefathers and overlapped with the inter textual and the popular images. 'Abakans' that is our world and inner-self at the same time might be a window through which she tries to show what the world is.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.161-163
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• 2021

In an apartment or private building, it is difficult for the user to operate the elevator button in a similar situation with luggage in both hands. In an environment where human contact must be minimized due to a highly infectious virus such as COVID-19, it is inevitable to operate an elevator based on untact. This paper proposes an operating system capable of operating the elevator by using the user's voice and image processing through the user's face without pressing the elevator button. The elevator can be operated to a designated floor without pressing a button by detecting the face of a person entering the elevator by detecting the person's face from the camera installed in the elevator, matching the information registered in advance. When it is difficult to recognize a person's face, it is intended to enhance the convenience of elevator use in an untouched environment by controlling the floor of the elevator using the user's voice through a microphone and automatically recording access information.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.5
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• pp.1296-1303
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• 2008

Recently, the university environment has been changed faster than before. It has based on university environment and IT infrastructure. Especially, most of local university has devised development plan such as improving the image and competitive power of campus. Digital, Electronic and Mobile Campus has increased the importance as people realize that the use of technology can improve the learning process. U-Campus of latest IT Technology need a service environment of which the practical use is possible through IT analysis of the members. For example u-campus setup of mobile offers the convenience to the members. We expected thing to use much, even though actual condition investigation about IT environment of the user is insufficient. The inconvenience of mobile could not be activated to the service for proactive use. The importance became the result about u-campus service setup of a company and university center. This service environment cannot offer specific information of center members for which the service implements. In this paper, we studied about members centralized u-campus model through u-recruit, campus information mobile service on university.