• Journal of the Korean Data and Information Science Society
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• v.25 no.2
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• pp.455-464
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• 2014

Unlabeled examples are easier and less expensive to obtain than labeled examples. Semisupervised approaches are used to utilize such examples in an eort to boost the predictive performance. This paper proposes a novel semisupervised classication method named transductive least squares support vector machine (TLS-SVM), which is based on the least squares support vector machine. The proposed method utilizes the dierence convex algorithm to derive nonconvex minimization solutions for the TLS-SVM. A generalized cross validation method is also developed to choose the hyperparameters that aect the performance of the TLS-SVM. The experimental results conrm the successful performance of the proposed TLS-SVM.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.1
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• pp.66-74
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• 1994

Gradient projection (GP) technique is applied for solving the optical routing problem (ORP) in high speed packet switched networks. The ORP minimizing average network packet loss probability is non-convex due to packet losses at intermediate switching nodes and its routing solution cannot be directly sought by the GP algorithm. Thus the non-convex ORP is transformed into a convex problem called the reduced-ORP (R-ORP) for which the GP algorithm can be used to obtain a routing solution. Through simulations, the routing solution of the R-ORP is shown to be a good approximation to that of the original ORP. Theoretical upper bound of difference between two (ORP and R-ORP) routing solutions is also derived.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2650-2667
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• 2021

In this paper, we derive the expression of the cache hitting probability with random caching policy and propose the joint optimization algorithm based on difference of convex algorithm (DCA) in the three-tier caching heterogeneous cellular network assisted by macro base stations, helpers and users. Under the constraint of the caching capacity of caching devices, we establish the optimization problem to maximize the cache hitting probability of the network. In order to solve this problem, a convex function is introduced to convert the nonconvex problem to a difference of convex (DC) problem and then we utilize DCA to obtain the optimal caching probability of macro base stations, helpers and users for each content respectively. Simulation results show that when the density of caching devices is relatively low, popular contents should be cached to achieve a good performance. However, when the density of caching devices is relatively high, each content ought to be cached evenly. The algorithm proposed in this paper can achieve the higher cache hitting probability with the same density.

• Journal of Information Display
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• v.3 no.2
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• pp.19-25
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• 2002

In this paper, a new target extraction algorithm is proposed, in which the coordinates of target are obtained adaptively by using the difference image information and the optical BPEJTC(binary phase extraction joint transform correlator) with which the target object can be segmented from the input image and background noises are removed in the stereo vision system. First, the proposed algorithm extracts the target object by removing the background noises through the difference image information of the sequential left images and then controlls the pan/tilt and convergence angle of the stereo camera by using the coordinates of the target position obtained from the optical BPEJTC between the extracted target image and the input image. From some experimental results, it is found that the proposed algorithm can extract the target object from the input image with background noises and then, effectively track the target object in real time. Finally, a possibility of implementation of the adaptive stereo object tracking system by using the proposed algorithm is also suggested.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.162-165
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• 2017

The proposed paper extracts the region of interest from the x-lay input image and compares it with the reference image. The x-ray image has the same shape, but the size, direction and position of the object are photographed differently. In this way, we measure the erection difference of darkness and darkness using the similarity measurement method for the same object. Distance measurement also calculates the distance between two points with vector coordinates (x, y, z) of x-lay data. Experimental results show that the proposed method improves the accuracy of ROI extraction and the reference image matching time is more efficient than the conventional method.

• Journal of Korea Multimedia Society
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• v.13 no.6
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• pp.825-832
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• 2010

This paper presents only a matching algorithm based on Delaunay triangulation and Parametrization from the extracted minutiae points. This method maps local neighborhood of points of two different point sets to unit-circle using topology information by Delaunay triangulation method from feature points of real fingerprint. Then, a linked convex polygon that includes an interior point is constructed as one-ring which is mapped to unit-circle using Parametrization that keep shape preserve. In local matching, each area of polygon in unit-circle is compared. If the difference of two areas are within tolerance, two polygons are consider to be matched and then translation, rotation and scaling factors for global matching are calculated.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.5 s.311
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• pp.12-21
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• 2006

In this paper, we propose a technique for extracting attentive objects in images using feature maps, regardless of the complexity of images and the position of objects. The proposed method uses feature maps with edge and color information in order to extract attentive objects. We also propose a reference map which is created by integrating feature maps. In order to create a reference map, feature maps which represent visually attentive regions in images are constructed. Three feature maps including edge map, CbCr map and H map are utilized. These maps contain the information about boundary regions by the difference of intensity or colors. Then the combination map which represents the meaningful boundary is created by integrating the reference map and feature maps. Since the combination map simply represents the boundary of objects we extract the candidate object regions including meaningful boundaries from the combination map. In order to extract candidate object regions, we use the convex hull algorithm. By applying a segmentation algorithm to the area of candidate regions to separate object regions and background regions, real object regions are extracted from the candidate object regions. Experiment results show that the proposed method extracts the attentive regions and attentive objects efficiently, with 84.3% Precision rate and 81.3% recall rate.

• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.522-532
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• 2011

In Oriental medicine, the status of a tongue is the important indicator to diagnose the condition of internal organs in a body. A tongue diagnosis is not only convenient but also non-invasive, and therefore widely used in Oriental medicine. But tongue diagnosis has some problems that should be objective and standardized, it also exhaust the diagnosis tool that can help for oriental medicine doctor's decision-making. In this paper, to solve the this problem we propose a method that calculates the tongue geometry information for effective tongue diagnosis analysis. Our method is to extract the tongue region for using improved snake algorithm, and calculates the geometry information by using convex hull and In-painting. In experiment, our method has stable performance as 7.2% by tooth plate and 8.5% by crack in region difference ratio.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1519-1522
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• 2002

In this paper, we propose a new adaptive dissolve detection method based on the analysis of a dissolve modeling error that is the difference between an ideally modeled dissolve curve without any correlation and an actual variance curve with a correlation. The dissolve modeling error is determined based on a correlation between two scenes and variances for each scene. First, Candidate regions are extracted by using the characteristics of a parabola that is downward convex, then the candidate region will be verified based on a dissolve modeling error. If a dissolve modeling error on a candidate region is less than a threshold that is defined by a dissolve modeling error with a target correlation, the candidate region should be a dissolve region with a correlation less than the target correlation. The threshold is adaptively determined based on the variances between the candidate regions and the target correlation. By considering the correlation between neighbor scenes, the proposed method is able to be a semantic scene-change detector. The proposed algorithm was tested on various types of data and its performance proved to be more accurate and reliable when compared with other commonly used methods