• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.5
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• pp.566-573
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• 2013

Inverse synthetic aperture radar(ISAR) images have been widely used in non-cooperative target recognition(NCTR). One of the most important issues in ISAR imaging is the improvement of the image smeared by target motion. In this paper, we propose the discrete Gabor representation(DGR) in an oversampling scheme for efficient acquisition of high-quality ISAR images. The DGR compartmentally assigns the Gabor coefficients to unit cells of the time-frequency grid related to the given Gabor logons. Thus, it can show an excellent time-frequency concentration and effectively discriminates the Doppler components from point-scatterers. The simulation results demonstrated that the DGR not only obtained high-quality ISAR images but also retained computational efficiency.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.19 no.3
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• pp.294-303
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• 2008

ISAR(Inverse Synthetic Aperture Radar) images represent the 2-D(two-dimensional) spatial distribution of RCS (Radar Cross Section) of an object, and they can be applied to the problem of target identification. A traditional approach to ISAR imaging is to use a 2-D IFFT(Inverse Fast Fourier Transform). However, the 2-D IFFT results in low resolution ISAR images especially when the measured frequency bandwidth and angular region are limited. In order to improve the resolution capability of the Fourier transform, various high-resolution spectral estimation approaches have been applied to obtain ISAR images, such as AR(Auto Regressive), MUSIC(Multiple Signal Classification) or Modified MUSIC algorithms. In this study, these high-resolution spectral estimators as well as 2-D IFFT approach are combined with a recently developed ISAR image classification algorithm, and their performances are carefully analyzed and compared in the framework of radar target recognition.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.2
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• pp.207-213
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• 2013

This study describes an omega-K algorithm for focusing bistatic synthetic aperture radar(SAR) data using bistatic-to-monostatic conversion. Bistatic SAR system considered in this study consists of a transmitting antenna and a physical array of several receiving antennas. The length of the physical array is identical to the SAR synthetic aperture. Unlike the monostatic case, an omega-K algorithm for the bistatic case is difficult to obtain the exact equation in the 2D wavenumber domain. The key of the proposed algorithm is converting the bistatic data into a monostatic one. The effectiveness of the proposed algorithm is proved by simulation and real measurement data.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.1
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• pp.104-114
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• 1999

This paper proposes an efficient method for the automatic generation of personalized 3D face model from color image sequence. To detect a robust facial region in a complex background, moving color detection technique based on he facial color distribution has been suggested. Color distribution and edge position information in the detected face region are used to extract the exact 31 facial feature points of the facial description parameter(FDP) proposed by MPEG-4 SNHC(Synthetic-Natural Hybrid Coding) adhoc group. Extracted feature points are then applied to the corresponding vertex points of the 3D generic face model composed of 1038 triangular mesh points. The personalized 3D face model can be generated automatically in less then 2 seconds on Pentium PC.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.2
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• pp.245-250
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• 2014

This paper introduces the inverse synthetic aperture radar(ISAR) imaging technique for rear view target of an automobile, which uses both linear frequency modulation-frequency shift keying(LFM-FSK) waveform and monopulse tracking. LFM-FSK waveform consists of two sequential stepped frequency waveforms with some frequency offset, and thus, can be used to generate ISAR images of rear view target of an automobile. However, ISAR images can often be blurred due to non-uniform change rate of relative aspect angle between radar and target. In order to address this problem, one-dimensional(1-D) Lagrange interpolation technique in conjunction with angle information obtained from the monopulse tracking is applied to generate uniform data across the radar's aspect angle. Simulation results show that the proposed method can provide focused ISAR images.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.8
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• pp.670-677
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• 2017

In this paper, we propose a rotational motion compensation(RMC) for bistatic inverse synthetic aperture radar(Bi-ISAR) imaging. For this purpose, geometry-error, caused by changes of bistatic-angle, is removed using known position information of a transmitter, a receiver, and target trajectories. Next, RMC is performed to compensate non-uniform rotational motion error by reformatting radar signal in terms of a newly defined slow time variable that converts non-uniform rotational motion into uniform one. Simulation results using an aircraft model composed of ideal point scatterers validate the efficacy of the proposed Bi-ISAR RMC method.

• Korean Journal of Radiology
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• v.25 no.3
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• pp.224-242
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• 2024

The emergence of Chat Generative Pre-trained Transformer (ChatGPT), a chatbot developed by OpenAI, has garnered interest in the application of generative artificial intelligence (AI) models in the medical field. This review summarizes different generative AI models and their potential applications in the field of medicine and explores the evolving landscape of Generative Adversarial Networks and diffusion models since the introduction of generative AI models. These models have made valuable contributions to the field of radiology. Furthermore, this review also explores the significance of synthetic data in addressing privacy concerns and augmenting data diversity and quality within the medical domain, in addition to emphasizing the role of inversion in the investigation of generative models and outlining an approach to replicate this process. We provide an overview of Large Language Models, such as GPTs and bidirectional encoder representations (BERTs), that focus on prominent representatives and discuss recent initiatives involving language-vision models in radiology, including innovative large language and vision assistant for biomedicine (LLaVa-Med), to illustrate their practical application. This comprehensive review offers insights into the wide-ranging applications of generative AI models in clinical research and emphasizes their transformative potential.

• Geophysics and Geophysical Exploration
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• v.8 no.4
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• pp.270-279
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• 2005

Under the research project supported by Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT), we have conducted the development of GPR systems for landmine detection. Until 2005, we have finished development of two prototype GPR systems, namely ALIS (Advanced Landmine Imaging System) and SAR-GPR (Synthetic Aperture Radar-Ground Penetrating Radar). ALIS is a novel landmine detection sensor system combined with a metal detector and GPR. This is a hand-held equipment, which has a sensor position tracking system, and can visualize the sensor output in real time. In order to achieve the sensor tracking system, ALIS needs only one CCD camera attached on the sensor handle. The CCD image is superimposed with the GPR and metal detector signal, and the detection and identification of buried targets is quite easy and reliable. Field evaluation test of ALIS was conducted in December 2004 in Afghanistan, and we demonstrated that it can detect buried antipersonnel landmines, and can also discriminate metal fragments from landmines. SAR-GPR (Synthetic Aperture Radar-Ground Penetrating Radar) is a machine mounted sensor system composed of B GPR and a metal detector. The GPR employs an array antenna for advanced signal processing for better subsurface imaging. SAR-GPR combined with synthetic aperture radar algorithm, can suppress clutter and can image buried objects in strongly inhomogeneous material. SAR-GPR is a stepped frequency radar system, whose RF component is a newly developed compact vector network analyzers. The size of the system is 30cm x 30cm x 30 cm, composed from six Vivaldi antennas and three vector network analyzers. The weight of the system is 17 kg, and it can be mounted on a robotic arm on a small unmanned vehicle. The field test of this system was carried out in March 2005 in Japan.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.11 no.7
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• pp.1258-1270
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• 2000

A synthetic aperture radar (SAR) system is able to provide all-weather, day-and-night, high resolution imaging capability in the wide area of interest, and thus is extremely useful in surveillance for both civil and military applications. In this paper, the X-band high-resolution spaceborne SAR system design is described with the key design parameters for the mission and system requirement characterized by the small satellite platform. The SAR imaging mode design technique is presented, and the standard imaging mode design results are analyzed with respect to image quality performance. In line with the system requirement, X-band SAR payload and ground reception/processing subsystems are designed and the key design results are demonstrated with the outstanding performance characteristics. The designed small satellite SAR system shows the wide range of imaging capability, and proves to be an effective surveillance systems in the light weight, high performance and cost-effective points of view.

• Conservation Science in Museum
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• v.29
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• pp.111-132
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• 2023

Terahertz radiation cannot pass through metal and therefore reflect and return most signals. Utilizing this property, this study analyzed information on paintings to verify the usage of metal materials on paintings and the scope of their application. First, the study tested specimens of metal-based pigments and synthetic pearl pigments with metallic colors and textures in order to compare basic characteristics of terahertz images, such as signal severance caused by metallic substances, traits reflected in cross-section images, and high degree of reflection. Subsequently, based on the collected information, the study diagnosed various types of paintings including Korean traditional paintings and oil paintings using the terahertz imaging technique to confirm the usage of metal-based pigments in the inner layers of paintings and their scope of application. The terahertz imaging technique could has the potential to provide scientific evidence for previously-undiscovered information and art-historical records about various types of paintings that used metalbased pigments, thereby rendering significant utility for the conservation and authentication of paintings.