• KIPS Transactions on Software and Data Engineering
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• v.12 no.12
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• pp.519-524
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• 2023

In hashing-based image retrieval, the hash code of a manipulated image is different from the original image, making it difficult to search for the same image. This paper proposes and evaluates a self-supervised deephashing model that generates perceptual hash codes from feature information such as texture, shape, and color of images. The comparison models are autoencoder-based variational inference models, but the encoder is designed with a fully connected layer, convolutional neural network, and transformer modules. The proposed model is a variational inference model that includes a SimAM module of extracting geometric patterns and positional relationships within images. The SimAM module can learn latent vectors highlighting objects or local regions through an energy function using the activation values of neurons and surrounding neurons. The proposed method is a representation learning model that can generate low-dimensional latent vectors from high-dimensional input images, and the latent vectors are binarized into distinguishable hash code. From the experimental results on public datasets such as CIFAR-10, ImageNet, and NUS-WIDE, the proposed model is superior to the comparative model and analyzed to have equivalent performance to the supervised learning-based deephashing model. The proposed model can be used in application systems that require low-dimensional representation of images, such as image search or copyright image determination.

• Progress in Medical Physics
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• v.25 no.4
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• pp.233-241
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• 2014

The aim of this study is to develop a new software tool for 3D dose verification using $PRESAGE^{REU}$ Gel dosimeter. The tool included following functions: importing 3D doses from treatment planning systems (TPS), importing 3D optical density (OD), converting ODs to doses, 3D registration between two volumetric data by translational and rotational transformations, and evaluation with 3D gamma index. To acquire correlation between ODs and doses, CT images of a $PRESAGE^{REU}$ Gel with cylindrical shape was acquired, and a volumetric modulated arc therapy (VMAT) plan was designed to give radiation doses from 1 Gy to 6 Gy to six disk-shaped virtual targets along z-axis. After the VMAT plan was delivered to the targets, 3D OD data were reconstructed from 512 projection data from $Vista^{TM}$ optical CT scanner (Modus Medical Devices Inc, Canada) per every 2 hours after irradiation. A curve for converting ODs to doses was derived by comparing TPS dose profile to OD profile along z-axis, and the 3D OD data were converted to the absorbed doses using the curve. Supra-linearity was observed between doses and ODs, and the ODs were decayed about 60% per 24 hours depending on their magnitudes. Measured doses from the $PRESAGE^{REU}$ Gel were well agreed with the TPS doses at central region, but large under-doses were observed at peripheral region at the cylindrical geometry. Gamma passing rate for 3D doses was 70.36% under the gamma criteria of 3% of dose difference and 3 mm of distance to agreement. The low passing rate was resulted from the mismatching of the refractive index between the PRESAGE gel and oil bath in the optical CT scanner. In conclusion, the developed software was useful for 3D dose verification from PRESAGE gel dosimetry, but further improvement of the Gel dosimetry system were required.

• Spatial Information Research
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• v.12 no.3
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• pp.285-298
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• 2004

Transportation digital map has built based on NGIS (national geography institute's 1 :5000 digital database) which derived from the aerial photo materials. Transportation digital map is a part of National Transportation Database Building Project carried out by the Korea Transport Institute and Ministry of Construction and Transportation. Transportation digital map for the purpose of transportation plan and investment has been updated and corrected the NGIS database especially for road network. Transportation digital map database is essential basic data fully applied for transportation policy and planning. The database must be reliable and objective to be applied for national transportation policy decision and transportation analysis. In addition, it needs accuracy and currentness to reflect the road network for the survey year. To satisfy the purpose of the database, following steps are necessary first, data Production and building has to be done by guideline of survey and database building. Secondly, geometric and logical errors which can occur during the survey and database building should be carefully detected. Thirdly, sectional guideline for database examination and procedure needs to be set up systematically and coherently This study is about examination guidelines for section and procedure on nodes and links which are essential object in transportation digital map database. According to the type of error, consistent and systematic error examination can lead to quality guarantee for objective and reliable database.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.4
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• pp.171-181
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• 2013

Recently, ground penetrating radar(GPR) has been widely used in detecting metallic and nonmetallic buried landmines and a number of related researches have been reported. A novel preprocessing method is proposed in this paper to flag potential locations of buried mine-like objects from GPR array measurements. GPR operates by measuring the reflection of an electromagnetic pulse from discontinuities in subsurface dielectric properties. As the GPR pulse propagates in the geologic medium, it suffers nonlinear attenuation as the result of absorption and dispersion, besides spherical divergence. In the proposed algorithm, a logarithmic transformed regression model which successfully represents the time-varying signal amplitude of the GPR data is estimated at first. Then, background signals may be densely distributed near the regression model and candidate signals of targets may be far away from the regression model in the time-amplitude space. Based on the observation, GPR signals are decomposed into candidate signals of targets and background signals using residuals computed from the estimated value by regression and the measurement of GPR. Candidate signals which may contain target signals and noise signals need to be refined. Finally, targets are detected through the refinement of candidate signals based on geometric signatures of mine-like objects. Our algorithm is evaluated using real GPR data obtained from indoor controlled environment and the experimental results demonstrate remarkable performance of our mine-like object detection method.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.6
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• pp.26-34
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• 2008

The information of traversability and path planning is essential for UGV(Unmanned Ground Vehicle) navigation. Such information can be obtained by analyzing 3D terrain. In this paper, we present the method of 3D terrain modeling with color information from a camera, precise distance information from a 2D Laser Range Finder(LRF) and wheel encoder information from mobile robot with less data. And also we present the method of 3B terrain modeling with the information from GPS/IMU and 2D LRF with less data. To fuse the color information from camera and distance information from 2D LRF, we obtain extrinsic parameters between a camera and LRF using planar pattern. We set up such a fused system on a mobile robot and make an experiment on indoor environment. And we make an experiment on outdoor environment to reconstruction 3D terrain with 2D LRF and GPS/IMU(Inertial Measurement Unit). The obtained 3D terrain model is based on points and requires large amount of data. To reduce the amount of data, we use cubic grid-based model instead of point-based model.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.4C
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• pp.117-125
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• 2011

The practical use of the electrical resistivity, which can makes the acquirement of the high resolution data in specific area, is increased in order to obtain a reasonable data for a ground investigation. The objective of this study is development of TRPF(Temperature-compensated Resistivity Probe for Field test), and an application in the field test for obtaining a reliable electrical resistivity value about considering the temperature effects. Temperature sensor is attached at 15mm, 30mm, 90mm below from the cone tip in consideration with the results of temperature transient process of cone probe and safety, and the angle of cone tip is $60^{\circ}$ for geometrical reason and minimizing the disturbance during the penetration test. Diameter of the cone probe is equally 35.7mm and penetration rate is 2 cm/sec for a comparison with standard cones such as CPT and SPT, and others. The temperature change is instantly observed around $4^{\circ}C$ when touching the ground, and the comparing results among the other cones indicates that the temperature compensation should be conducted in the ground survey using the electrical resistivity. This study shows that the necessity of temperature effects compensation during penetration test through the development and field verification of TRPF (Temperature-compensated Resistivity Probe for Field test).

• Journal of Broadcast Engineering
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• v.25 no.2
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• pp.166-175
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• 2020

Recently, application fields for processing and using digital image contents in various forms and types are rapidly increasing. Since image content is high value-added content, the intellectual property rights of this content must be protected in order to activate the production and use of the digital image content. In this paper, we propose a deep learning based watermark embedding and extraction network. The proposed method is to maximize the robustness of the watermark against malicious/non-malicious attacks while preserving the invisibility of the host image. This network consists of a preprocessing network that changes the watermark to have the same resolution as the host image, a watermark embedding network that embeds watermark data while maintaining the resolution of the host image by three-dimensionally concatenating the changed host image and the watermark information, and a watermark extraction network that reduces the resolution and extracts watermarks. This network verifies the invisibility and robustness of the proposed method by experimenting with various pixel value change attacks and geometric attacks against various watermark data and host images with various resolutions, and shows that this method is universal and practical.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2014.06a
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• pp.107-108
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• 2014

As the demand for precise navigation has increased, more focus is put on the precise positioning, RTK(Real Time Kinematics) which has been used in the surveying field. The Position of Single Reference Station RTK or two-way network RTK such as VRS (Virtual Reference Station) is accurate enough to be used as a main technology in land surveying, however its service area and number of users is limited and the users are assumed static. This characteristic is not suitable to the navigation, whose service target is infinite number of users moving over a wide area. One-way network RTK has recently been suggested as a solution for the precise navigation technique for the mobile user. This paper shows the performance prediction of the one-way network RTK such as MAC(Master-Auxiliary Concept), or FKP (Flachenkorrekturparameter). To show the performance variation by the rover position, we constructed a simulation data of users on the grid with 0.1 degree spacing between 36.5 and 37 degree latitude and between 127 and 127.5 degree longitude.

• Progress in Medical Physics
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• v.20 no.2
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• pp.51-61
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• 2009

A Compton camera, which is based on the geometrical interpretation of Compton scattering, is a very promising gamma-ray imaging device considering its several advantages over the conventional gamma-ray imaging devices: high imaging sensitivity, 3-D imaging capability from a fixed position, multi-tracing functionality, and almost no limitation in photon energy. In the present study, a Monte Carlo-based, user-friendly Compton imaging simulator was developed in the form of a graphical user interface (GUI) based on Geant4 and $MATLAB^{TM}$. The simulator was tested against the experimental result of the double-scattering Compton camera, which is under development at Hanyang University in Korea. The imaging resolution of the simulated Compton image well agreed with that of the measured image. The imaging sensitivity of the measured data was 2~3 times higher than that of the simulated data, which is due to the fact that the measured data contains the random coincidence events. The performance of a stacking-structure type Compton camera was evaluated by using the simulator. The result shows that the Compton camera shows its highest performance when it uses 4 layers of scatterer detectors.

• The Journal of Engineering Geology
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• v.25 no.2
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• pp.227-235
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• 2015

In recent years, owing to the frequent occurrence of natural disasters, the inspection and maintenance of structures have become increasingly important on a national scale. However, because most structural inspections are carried out manually, and due to the lack of objectivity in data acquisition, quantitative data are not always available. As a result, researchers are seeking ways to collect and standardize survey data using terrestrial laser scanning, thereby bypassing the limitations associated with visual investigations. However, field data acquired using a laser scanner have been required to measure changes in structure geometry resulting from passive deterioration. In this study, we demonstrate that it is possible to identify the processes of structural deterioration (e.g., efflorescence, leakage, delamination) using intensity data from terrestrial laser scanning. Additionally, we confirm the viability of automated classification of alteration type and objectification of the polygon area by establishing intensity characteristics. Finally, we show that our method is effective for structural inspection and maintenance.