• Title/Summary/Keyword: Image Transfer

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Two-dimensional / Three-dimensional convertible modified integral imaging system using functional polarizing film (기능성 편광필름을 이용한 2차원/3차원 전환가능 변형 집적 영상 시스템)

  • Song, Byeong-Seop;Park, Sun-Gi;Min, Seong-Uk
    • Proceedings of the Optical Society of Korea Conference
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    • 2009.10a
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    • pp.6-7
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    • 2009
  • We proposed the two-dimensional (2D) / three-dimensional (3D) convertible modified integral imaging system using functional polarizing film named $imazer^{TM}$, which transfer or scatter the incident light ray according to the polarizing direction of ray. When the incident light rays transfer to $imazer^{TM}$, the rays generate 3D image through the process of the modified integral imaging system. However, the scattered light rays generate 2D image through the simple backlight scheme when the incident rays are scattered by the film. The proposed method can be implemented the partial 3D display system without any mechanical movements. In this paper, we propose and verify our system using some basic experiments and its results.

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A Study on 3D View Design of Images and Voices Integration for Effective Information Transfer (효과적 정보전달을 위한 영상정보의 3D 뷰 및 음성정보와의 융합 연구)

  • Shin, C.H.;Lee, J.S.
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.35 no.1B
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    • pp.35-41
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    • 2010
  • In this paper, we propose a 3D view design scheme which arranges 2D information in a 3D virtual space with a flexible interface and voice information. The scheme allows the user interface of the 2D image in 3D virtual space anytime from any view point. Voice information can be easily attached. It is this simple and efficient image and voice information arrangement in 3D virtual space that improves information transfer.

Image Signal Transfer Method in Artificial Retina using Laser (레이저를 이용한 인공망막에서의 영상 신호 전달방법)

  • Yun, Il-Yong;Lee, Byeong-Ho;Kim, Seong-Jun
    • The Transactions of the Korean Institute of Electrical Engineers C
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    • v.51 no.5
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    • pp.222-227
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    • 2002
  • Recently, the research on artificial retina for the blind is active. In this paper a new optical link method for the retinal prosthesis is proposed. Laser diode system was chosen to transfer image into the eye in this project and the new optical system was designed and evaluated. The use of laser diode array in artificial retina system makes system simple for lack of signal processing part inside of the eyeball. Designed optical system is enough to focus laser diode array on photodiode array in 20$\times$20 application.

Emotional Image Color Transfer via Voice Emotion Analytics System Based on Raspberry Pi (라즈베리 파이 기반의 음성 감정 분석 시스템을 통한 감성적 이미지 색상 전달)

  • Kim, Jong-Hyun
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2019.01a
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    • pp.391-393
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    • 2019
  • 본 논문은 일상적인 대화로부터 감성을 추출하고 분석함으로써 상황에 맞는 대화의 내용과 분위기를 이미지의 색상으로 표현할 수 있는 이미지 색상 변환 프레임워크를 소개한다. 본 연구는 라즈베리 파이와 마이크 센서를 기반으로 사용자로부터 목소리를 입력받을 수 있는 모듈을 제작하고, 그 목소리로부터 감성을 분석한다. 분석된 감성을 이용하여 이미지의 색상을 자동으로 변환하는 기술과 통합함으로써 청각장애인 및 미취학 아동들이 화자의 대화를 이미지를 통해 쉽게 인지하여 의사소통 및 감성 전달 환경을 개선하고자 한다.

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Automatic Child Image Classification System Through Transfer Learning (전이학습을 통한 아동 이미지 자동 분류 시스템)

  • Kim, Wooseong;Moon, Mikyeong
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2021.07a
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    • pp.551-552
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    • 2021
  • 인공지능 기술의 발달로 현대사회 사람들은 일상생활에 편리함을 제공받고 업무의 효율성과 생산성이 향상되었다. 대한민국 보육교사들은 수많은 업무로 인해 근무시간 대비 휴식시간과 점심시간이 턱없이 부족하다. 본 논문에서는 보육교사가 일일이 아동들의 사진을 분류하는 업무에 편의성을 제공하여 보다 많은 휴식시간을 보장받고 활용할 수 있도록 전이학습을 통한 아동 이미지 자동 분류 시스템에 대해 기술하고자 한다. 이 시스템을 통해 분류된 아동들의 사진을 매년 제작하는 유아 포토북 제작에도 활용할 수 있을 것으로 기대된다.

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A Study on the Construction of Image Datasets for Object Detection of Painting Cultural Heritage (회화문화재 객체검출을 위한 학습용 이미지 데이터셋 구축 방안 연구)

  • Kwon, Do-Hyung;Yu, Jeong-Min
    • Proceedings of the Korea Information Processing Society Conference
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    • 2021.11a
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    • pp.853-855
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    • 2021
  • 본 연구는 회화문화재 속에 표현된 다양한 종류의 객체를 검출할 수 있는 딥러닝 모델생성을 위해 필요한 학습용 이미지 데이터셋 구축방안을 제안한다. 먼저 기존 동양화 기반의 회화문화재 이미지 데이터 및 객체 특징 분석을 진행하였고, 이를 바탕으로 Natural image에 Pose transfer 및 Style transfer를 적용한 새로운 방식의 회화문화재 이미지 데이터 생성 방법을 제안한다. 제안한 프레임워크를 통해 기존 문화재 분야에서 가지고 있던 제한된 데이터 구축문제를 극복하고, 검출모델 생성을 위한 대용량의 학습데이터 구축 가능성을 제시하였다.

Early Detection of Rice Leaf Blast Disease using Deep-Learning Techniques

  • Syed Rehan Shah;Syed Muhammad Waqas Shah;Hadia Bibi;Mirza Murad Baig
    • International Journal of Computer Science & Network Security
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    • v.24 no.4
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    • pp.211-221
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    • 2024
  • Pakistan is a top producer and exporter of high-quality rice, but traditional methods are still being used for detecting rice diseases. This research project developed an automated rice blast disease diagnosis technique based on deep learning, image processing, and transfer learning with pre-trained models such as Inception V3, VGG16, VGG19, and ResNet50. The modified connection skipping ResNet 50 had the highest accuracy of 99.16%, while the other models achieved 98.16%, 98.47%, and 98.56%, respectively. In addition, CNN and an ensemble model K-nearest neighbor were explored for disease prediction, and the study demonstrated superior performance and disease prediction using recommended web-app approaches.

Evaluation of Noise Power Spectrum Characteristics by Using Magnetic Resonance Imaging 3.0T (3.0T 자기공명영상을 이용한 잡음전력스펙트럼 특성 평가)

  • Min, Jung-Whan;Jeong, Hoi-Woun;Kim, Seung-Chul
    • Journal of radiological science and technology
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    • v.44 no.1
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    • pp.31-37
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    • 2021
  • This study aim of quantitative assessment of Noise Power Spectrum(NPS) and image characteristics of by acquired the optimal image for noise characteristics and quality assurance by using magnetic resonance imaging(MRI). MRI device was (MAGNETOM Vida 3.0T MRI; Siemense healthcare system; Germany) used and the head/neck shim MR receive coil were 20 channels coil and a diameter 200 mm hemisphere phantom. Frequency signal could be acquired the K-space trajectory image and white image for NPS. The T2 image highest quantitatively value for NPS finding of showed the best value of 0.026 based on the T2 frequency of 1.0 mm-1. The NPS acquired of showed that the T1 CE turbo image was 0.077, the T1 CE Conca2 turbo image was 0.056, T1 turbo image was 0.061, and the T1 Conca2 turbo image was 0.066. The assessment of NPS image characteristics of this study were to that could be used efficiently of the MRI and to present the quantitative evaluation methods and image noise characteristics of 3.0T MRI.

The Optimal Design of POF Optical Connector for Medical Image Transmission System (의료영상전송시스템을 위한 POF 광커넥터의 최적 설계)

  • Cheon, Min-Woo;Cho, Kyung-Jae;Park, Yong-Pil
    • Journal of the Korean Institute of Electrical and Electronic Material Engineers
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    • v.23 no.12
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    • pp.978-982
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    • 2010
  • For mass information transfer, the optical communication using optic fiber has been widely used. Especially, in the field of medical image, the large data is digitalized based on the standard image and it is used for telemedicine with this method. Therefore, to transfer the large amount of data fast and effectively POF (Plastic Optical Fiber) can be used and the development of optic connector for connection between POFs is very important. In this study, for stable optical coupling of POF optic fiber Ferrule and Sleeve were designed and produced by considering the bond stability and the insertion loss according to the physical contact and roughness profile was evaluated. As a result of examining the insertion loss by physical contact method of two optic fibers, it showed the loss was about 1.895dB. According to the results from studying the condition of grinding section for POF mass production, the mass production condition was established as POF profile roughness of 6nm and the loss of 0.2dB or lower by controlling the film size and time step by step.

Performance Comparison of Gas Leak Region Segmentation Based on Transfer Learning (Transfer Learning 기법을 이용한 가스 누출 영역 분할 성능 비교)

  • Marshall, Marshall;Park, Jang-Sik;Park, Seong-Mi
    • Journal of the Korean Society of Industry Convergence
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    • v.23 no.3
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    • pp.481-489
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    • 2020
  • Safety and security during the handling of hazardous materials is a great concern for anyone in the field. One driving point in the security field is the ability to detect the source of the danger and take action against it as quickly as possible. Via the usage of a fully convolutional network, it is possible to create the label map of an input image, indicating what object is occupying the specific area of the image. This research employs the usage of U-net, which was constructed in biomedical field segmentation to segment cells, instead of the original FCN. One of the challenges that this research faces is the availability of ground truth with precise labeling for the dataset. Testing the network after training resulted in some images where the network pronounces even better detail than the expected label map. With better detailed label map, the network might be able to produce better segmentation is something to be studied in further research.