• Proceedings of the KSRS Conference
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• v.2
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• pp.713-716
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• 2006

The technique of the information communication are advanced recently and a performance enhance of a hand carried computing device was developed rapidly. Mobile Communication Carrier developed currently the phone navigation and are carrying out the service. But such service localizes at the vehicle movement. In This paper, we explain a system structure for the pedestrian navigation of the Wireless Internet Platform for Interoperability(WIPI) mobile phone which contains the MS-Based Global Positioning System(GPS) internally. And we verified the result to be developed by this method that proposes.

• ETRI Journal
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• v.41 no.6
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• pp.750-759
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• 2019

Presently, the extraction of hand-crafted features is still the dominant method in radar emitter recognition. To solve the complicated problems of selection and updation of empirical features, we present a novel automatic feature extraction structure based on deep learning. In particular, a convolutional neural network (CNN) is adopted to extract high-level abstract representations from the time-frequency images of emitter signals. Thus, the redundant process of designing discriminative features can be avoided. Furthermore, to address the performance degradation of a single platform, we propose the construction of an ensemble learning-based architecture for multi-platform fusion recognition. Experimental results indicate that the proposed algorithms are feasible and effective, and they outperform other typical feature extraction and fusion recognition methods in terms of accuracy. Moreover, the proposed structure could be extended to other prevalent ensemble learning alternatives.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.4
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• pp.403-411
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• 2010

This research demonstrates a 3D virtual visualization of urban environment and video fusion for effective damage prevention and surveillance system using open standard. We present the visualization and interaction simulation method to increase the situational awareness and optimize the realization of environmental monitoring through the CCTV video and 3D virtual environment. New camera prototype was designed based on the camera frustum view model to project recorded video prospectively onto the virtual 3D environment. The demonstration was developed by the X3D, which is royalty-free open standard and run-time architecture, and it offers abilities to represent, control and share 3D spatial information via the internet browsers.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.1004-1006
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• 2019

Different scale of information is an important component in computer vision systems. Recently, there are considerable researches on utilizing multi-scale information to solve the scale-invariant problems, such as GoogLeNet and FPN. In this paper, we introduce the notion of different scale information fusion (DSIF) and show that it has a significant effect on the performance of object recognition systems. We analyze the DSIF in several architecture designs, and the effect of nonlinear activations, dropout, sub-sampling and skip connections on it. This leads to clear suggestions for ways of the DSIF to choose.

• Journal of Korea Multimedia Society
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• v.24 no.1
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• pp.1-12
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• 2021

In this paper, we present a new architecture for semantic segmentation. Semantic segmentation aims at a pixel-wise classification which is important to fully understand images. Previous semantic segmentation networks use features of multi-layers in the encoder to predict final results. However, they do not contain various receptive fields in the multi-layers features, which easily lead to inaccurate results for boundaries between different classes and small objects. To solve this problem, we propose a multi-path feature fusion module that allows for features of each layers to contain various receptive fields by use of a set of dilated convolutions with different dilatation rates. Various experiments demonstrate that our method outperforms previous methods in terms of mean intersection over unit (mIoU).

• Journal of the Korean Society for Precision Engineering
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• v.27 no.2
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• pp.130-136
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• 2010

For stability analysis of the lumbar spine, the hypothesis presented is that the disc has stress sensors driving feedback mechanism, which could react to the imposed loads by adjusting the contraction of the muscles. Fusion in the motion segment of the lumbar spinal column is believed to alter the stability of the spinal column. To identify this effect finite element (FE) models combined with optimization technique was applied and quantify the role of each muscle and reaction forces in the spinal column with respect to the fusion level. The musculoskeletal FE model was consisted with detailed whole lumbar spine, pelvis, sacrum, coccyx and simplified trunk model. Vertebral body and pelvis were modeled as a rigid body and the rib cage was constructed with rigid truss element for the computational efficiency. Spinal fusion model was applied to L3-L4, L4-L5, L5-S1 (single level) and L3-L5 (two levels) segments. Muscle architecture with 46 local muscles was used as acting directions. Minimization of the nucleus pressure deviation and annulus fiber average axial stress deviation was selected for cost function. As a result, spinal fusion produced reaction changes at each motion segment as well as contribution of each muscle. Longissimus thoracis and psoas major muscle showed dramatic changes for the cases of L5-S1 and L3-L5 level fusion. Muscle force change at each muscle also generated relatively high nucleus pressure not only at the adjacent level but at another level, which can explain disc degeneration pattern observed in clinical study.

• Smart Structures and Systems
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• v.29 no.1
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• pp.221-235
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• 2022

Manual inspection of steel box girders on long span bridges is time-consuming and labor-intensive. The quality of inspection relies on the subjective judgements of the inspectors. This study proposes an automated approach to detect and segment cracks in high-resolution images. An end-to-end cascaded framework is proposed to first detect the existence of cracks using a deep convolutional neural network (CNN) and then segment the crack using a modified U-Net encoder-decoder architecture. A Naïve Bayes data fusion scheme is proposed to reduce the false positives and false negatives effectively. To generate the binary crack mask, first, the original images are divided into 448 × 448 overlapping image patches where these image patches are classified as cracks versus non-cracks using a deep CNN. Next, a modified U-Net is trained from scratch using only the crack patches for segmentation. A customized loss function that consists of binary cross entropy loss and the Dice loss is introduced to enhance the segmentation performance. Additionally, a Naïve Bayes fusion strategy is employed to integrate the crack score maps from different overlapping crack patches and to decide whether a pixel is crack or not. Comprehensive experiments have demonstrated that the proposed approach achieves an 81.71% mean intersection over union (mIoU) score across 5 different training/test splits, which is 7.29% higher than the baseline reference implemented with the original U-Net.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.1
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• pp.154-166
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• 2016

This study aims to contribute to better understanding the effects of the changes in the parameter values of GroundFilter algorithm(GF), which performs filtering process, and of GridsurfaceCreate algorithm(GC), which creates regular grid, provided in Fusion software on the accuracy of elevation of the final LiDAR-DEM products through comparative analysis. In order to test whether there are significant effects on the accuracy of the final LiDAR-DEM products due to the changes of GF(1, 3, 5, 7, 9) parameter levels and GC(1, 3, 5, 7, 9) parameter levels, two-way ANOVA is conducted based on residuals. The residuals are calculated using the differences between each sample plot's paired field-measured and DEM-derived elevation values given each individual GF and GC level. After that, Tukey HSD test is conducted as a post hoc test for grouping the levels. As a result of two-way ANOVA test, it is found that the change in the GF levels significantly affects the accuracy of LiDAR-DEM elevations(F-value : 27.340, p < 0.01), while the change in the GC levels does not significantly affect the accuracy of LiDAR-DEM elevations(F-value : 0.457). It is also found that the interaction effect between GF and GC levels is not likely to exist(F-value : 0.247). From the results of the Tukey HSD test in the GF levels, GF levels can be divided into two groups('7', '5', '9', '3' vs '1') by the differences of means of residuals. Given the current conditions, LiDAR-DEM can achieve the best accuracy when the level '7' and '3' are given as GF and GC level, respectively.

• Korean Institute of Interior Design Journal
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• no.40
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• pp.26-33
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• 2003

Contemporary architecture has two different movements that one is the utilization of digital technology and the other is the inclination to nature. After deconstructivism in architecture, the tendency of design shows the fusion between digitalism and organicism and as a consequence the phenomena of 'skin expression' has emerged which can be thought as 'organic digitalism' or 'digital organicism'. The definition of skin tendency in environmental design is the design of nature based on the technology. As a result, the surface becomes the design issue compared to structure and the momentum for new aesthetic value. There are post-structuralism, complex system theory and the organic architecture as theoretical background for the tendency of skin expression. Specially the ideas of post-structural philosophy has effected deeply to the formation of its movement and also offered the theoretical nutrition for digital architecture. The characteristics of the skin tendency can be analyzed as topological transformation, smooth continuum, deterritorialization, ecological response system, and tactility. These design characteristics has combined with conventional material and design vocabulary to transform and develope new spatial conception.

• Journal of architectural history
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• v.8 no.2 s.19
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• pp.109-118
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• 1999

The purpose of this paper is to apply Stephen C. Pepper's contextualism to architecture: to interpret the former in the light of architectural theory, and ultimately to liberate architecture from the Western 'Idea' and return it to its context. The major concepts of Pepper used in the paper are quality, texture, spread, change, fusion, strand and context. Pepper's contextualism makes us realize that architecture cannot be separated from its context where human beings, history, neighborhood, and nature are all interpenetrating, and create a quality. Contextualism thus teaches us to make an effort to understand the region where we belong, and to create an architectural device that interrelates form and function of an architecture with its space-time environment, or its strand, texture and context.