• Spatial Information Research
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• v.11 no.4
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• pp.509-518
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• 2003

Impervious surface affects urban climate, flood, and water pollution. With a higher paved rate, expanded heat containing capacity of buildings and roads raises atmospheric temperature, and increased quantity of the outflowed water brings flood during a heavy downpour. Moreover, increased non-point source pollutant load is accountable for water pollution. In this regard, it is definitely important to research and keep monitoring the current situation of paved surface, which influences urban ecosystem, disaster and pollution. In fact, collecting information on urban paved surface, which requires the time and expense, is very difficult due to its complicate structure. In order to solve the problem, this study suggested a method to utilize satellite image data for efficient survey on the current condition of paved surface. It analyzed the paved surface condition of Anyang-si by using IKONOS image and discussed the usefulness and limitation of this method.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.588-595
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• 2003

High resolution panchromatic satellite images collected by sensors such as IRS-1C/D and KOMPSAT-1 have a spatial resolution of approximately 6 ${\times}$ 6 ㎡, making them very attractive for urban applications. However, the spectral information present in these images is very limited. In order to overcome this limitation, an object-oriented classification approach is used to identify basic land cover types in urban areas. Before an image can be classified it is segmented at different aggregation levels using a multiresolution segmentation approach. In the course of this segmentation various statistical as well as topological information is collected for each segment. Based on this information it is possible to classify image objects and to arrive at much better results than by looking only at single pixels. Using an image recorded by KOMPSAT-1 over the City of Vienna a land cover classification was carried out for two areas. One was used to set up the rules for the different land cover types. The second subset was classified based on these rules, only adjusting some of the functions governing the classification process.

• Korean Journal of Construction Engineering and Management
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• v.12 no.3
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• pp.131-139
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• 2011

In this Study, the Cost of Public Facility Construction in the VE Cost Model, and the Progress of the Construction Site Management, and Cost due to the Lack of Cpatial Information in Dispute Cost Work Type Recognize the limits of Historical Information, and to Overcome the Perception of Cost and Space Systems Unit In the Process of Transition that Began Seeking Ways to Improve Through this Study, Different Parts of the Proposed Area of Construction Work Unit System, the Core of Calculating Hourly and Detailed Engineering Information and Cost Information Generated Extension to Configure the Construction Unit in Every Space, Every Work Unit System, All Materials That Make Up Work Unit System, Unit Labor Costs, And All of the Configuration Items Enables Precise And Multidimensional Understanding is That.

• Journal of Chest Surgery
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• v.21 no.2
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• pp.223-230
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• 1988

Emax, end-systolic pressure-volume relationship, has been established as a new concept which can be representative of ventricular contractility itself since 1970s. Comparing to ejection fraction[EF], Emax is independent of preload and afterload. However Emax has not been proved precisely in non-thoracotomized condition because current methods have limitation in measuring ventricular chamber volume accurately in in viva state. The Dynamic Spatial Reconstructor[DSR], high speed computerized tomography, can measure ventricular chamber volume accurately throughout cardiac cycle in non-thoracotomized state. So Emax and EF of the left ventricle was tried to measure precisely in in vivo condition with DSR. Emax was compared to EF to estimate its ability to evaluate ventricular contractility. 5 mongrel dogs, weighing 15-16kg, were used for measuring Emax and EF of the left ventricle in 3 or 4 different loading conditions using DSR. Emax value in 5 dogs was from 2.62 to 10.49. Each dog has one Emax value regardless of loading conditions. However EF in 5 dogs varies depending on loading conditions. The conclusions are that Emax is useful in in viva state and EF varies depending on loading conditions. So Emax should be tried to use in clinical situation rather than EF because it is always representative of contractility itself regardless loading conditions in in viva state.

• Journal of The Korea Institute of Healthcare Architecture
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• v.13 no.3
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• pp.7-14
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• 2007

The concept and spatial composition of office have endlessly changed according to social trend. And according to social change, members of office, namely, concept of organization has been changed. Presently, our society finds and needs appearance of office suitable for our society. According to a concept of ecological environment and a concept laying stress on human, various trials have been performed but still, stress of salaried men is treated as social issue. By having connection between psychological healing theory of Max $L{\ddot{\bar{u}}}scher$ and spatial expression elements (content : refuge, self-esteem : prospect, confidence : flow, liberty : void) as a theory, we discussed possibility of aesthetic office landscape could be developed to a type of office which could control emotion that can be a cause of stress and we intended to examine limitation and possibility through case analysis.

• Journal of the Society of Naval Architects of Korea
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• v.54 no.2
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• pp.83-89
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• 2017

Numerical simulations of ship resistance have been performed to compare spatial characteristics of Courant number when using structured and unstructured meshes. When Euler scheme was used for time integration, the structured mesh provided a more efficient calculation because the calculation time interval was larger than that of unstructured mesh. The automatic generation of very small meshes in the unstructured mesh was mainly responsible for the limitation of calculation time interval. When local time stepping Euler scheme was applied, however, the ship resistance of unstructured mesh showed a rapid convergence while a slow convergence of ship resistance in structured mesh was caused by the small time interval in bulbous bow.

• Journal of Korea Multimedia Society
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• v.19 no.9
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• pp.1647-1658
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• 2016

RGB+D database has been widely used in object recognition, object tracking, robot control, to name a few. While rapid advance of active depth sensing technologies allows for the widespread of indoor RGB+D databases, there are only few outdoor RGB+D databases largely due to an inherent limitation of active depth cameras. In this paper, we propose a novel method used to build outdoor RGB+D databases. Instead of using active depth cameras such as Kinect or LIDAR, we acquire a pair of stereo image using high-resolution stereo camera and then obtain a depth map by applying stereo matching algorithm. To deal with estimation errors that inevitably exist in the depth map obtained from stereo matching methods, we develop an approach that estimates confidence of depth maps based on unsupervised learning. Unlike existing confidence estimation approaches, we explicitly consider a spatial correlation that may exist in the confidence map. Specifically, we focus on refining confidence feature with the assumption that the confidence feature and resultant confidence map are smoothly-varying in spatial domain and are highly correlated to each other. Experimental result shows that the proposed method outperforms existing confidence measure based approaches in various benchmark dataset.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.127-136
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• 2021

Real-time human recognition is a challenging task, as the images are captured in an unconstrained environment with different poses, makeups, and styles. This limitation is addressed by generating several facial images with poses, makeup, and styles with a single reference image of a person using Generative Adversarial Networks (GAN). In this paper, we propose deep learning-based human recognition using integration of GAN and Spatial Domain Techniques. A novel concept of human recognition based on face depiction approach by generating several dissimilar face images from single reference face image using Domain Transfer Generative Adversarial Networks (DT-GAN) combined with feature extraction techniques such as Local Binary Pattern (LBP) and Histogram is deliberated. The Euclidean Distance (ED) is used in the matching section for comparison of features to test the performance of the method. A database of millions of people with a single reference face image per person, instead of multiple reference face images, is created and saved on the centralized server, which helps to reduce memory load on the centralized server. It is noticed that the recognition accuracy is 100% for smaller size datasets and a little less accuracy for larger size datasets and also, results are compared with present methods to show the superiority of proposed method.

• Journal of Korea Multimedia Society
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• v.24 no.2
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• pp.178-185
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• 2021

Three-dimensional high-resolution magnetic resonance imaging (MRI) provides fine-level anatomical information for disease diagnosis. However, there is a limitation in obtaining high resolution due to the long scan time for wide spatial coverage. Therefore, in order to obtain a clear high-resolution(HR) image in a wide spatial coverage, a super-resolution technology that converts a low-resolution(LR) MRI image into a high-resolution is required. In this paper, we propose a super-resolution technique through filter learning based on information on the surrounding gradient information in 3D space from 3D MRI images. In the learning step, the gradient features of each voxel are computed through eigen-decomposition from 3D patch. Based on these features, we get the learned filters that minimize the difference of intensity between pairs of LR and HR images for similar features. In test step, the gradient feature of the patch is obtained for each voxel, and the filter is applied by selecting a filter corresponding to the feature closest to it. As a result of learning 100 T1 brain MRI images of HCP which is publicly opened, we showed that the performance improved by up to about 11% compared to the traditional interpolation method.

• The KIPS Transactions:PartB
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• v.18B no.6
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• pp.365-374
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• 2011

Recently, malicious video classification and filtering techniques are of practical interest as ones can easily access to malicious multimedia contents through the Internet, IPTV, online social network, and etc. Considerable research efforts have been made to developing malicious video classification and filtering systems. However, the malicious video classification and filtering is not still being from mature in terms of reliable classification/filtering performance. In particular, the most of conventional approaches have been limited to using only the spatial features (such as a ratio of skin regions and bag of visual words) for the purpose of malicious image classification. Hence, previous approaches have been restricted to achieving acceptable classification and filtering performance. In order to overcome the aforementioned limitation, we propose new malicious video classification framework that takes advantage of using both the spatial and temporal features that are readily extracted from a sequence of video frames. In particular, we develop the effective temporal features based on the motion periodicity feature and temporal correlation. In addition, to exploit the best data fusion approach aiming to combine the spatial and temporal features, the representative data fusion approaches are applied to the proposed framework. To demonstrate the effectiveness of our method, we collect 200 sexual intercourse videos and 200 non-sexual intercourse videos. Experimental results show that the proposed method increases 3.75% (from 92.25% to 96%) for classification of sexual intercourse video in terms of accuracy. Further, based on our experimental results, feature-level fusion approach (for fusing spatial and temporal features) is found to achieve the best classification accuracy.