• Journal of the Korean Data and Information Science Society
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• v.25 no.5
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• pp.1107-1116
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• 2014

In this paper, we review recent developments in network analysis using the graph theory, and introduce ongoing research area with relevant theoretical results. In specific, we introduce basic notations in graph, and conditional and marginal approach in constructing the adjacency matrix. Also, we introduce the Marcenko-Pastur law, the Tracy-Widom law, the white Wishart distribution, and the spiked distribution. Finally, we mention the relationship between degrees and eigenvalues for the detection of hubs in a network.

• Korean Journal of Remote Sensing
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• v.27 no.6
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• pp.717-728
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• 2011

An efficient method for the unsupervised classification of high resolution imagery is suggested in this paper. It employs pixel-linking and merging based on the adjacency graph. The proposed algorithm uses the neighbor lines of 8 directions to include information in spatial proximity. Two approaches are suggested to employ neighbor lines in the linking. One is to compute the dissimilarity measure for the pixel-linking using information from the best lines with the smallest non. The other is to select the best directions for the dissimilarity measure by comparing the non-homogeneity of each line in the same direction of two adjacent pixels. The resultant partition of pixel-linking is segmented and classified by the merging based on the regional and spectral adjacency graphs. This study performed extensive experiments using simulation data and a real high resolution data of IKONOS. The experimental results show that the new approach proposed in this study is quite effective to provide segments of high quality for object-based analysis and proper land-cover map for high resolution imagery of urban area.

• Journal of Broadcast Engineering
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• v.22 no.4
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• pp.473-483
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• 2017

Since the advent of 3D and UHD contents, demand for high-quality panoramic images has been increasing. The UWV(Ultra-Wide Viewing) service uses a wider viewing angle than conventional panoramas to provide a lively experience for users and enhance their understanding of the event. In this paper, we propose a spatial adjacency map generation method and an UWV file storage format technology to provide UWV service. The spatial adjacency map measures the similarity between images and generate the position information of the images based on similarity. And the stitching time of the image can be shortened through the generated position information. Through the spatial adjacency map, we generate the large screen content quickly. The UWV file format which is based on ISOBMFF process spatial adjacency map and videos and support random access. In this paper, we design the UWV player to verify the spatial adjacency map and UWV file format and show the result of experiments.

• Journal of the Korean Data and Information Science Society
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• v.22 no.1
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• pp.19-27
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• 2011

Recommendation systems are developed to overcome the problems of selection and to promote intention to use. In this study, we propose a recommendation system using adjacency data according to user's behavior over time. For this, the product adjacencies are identified from the adjacency matrix based on graph theory. This research finds that there is a trend in the users' behavior over time though product adjacency fluctuates over time. The system is tested on its usability. The tests show that implementing this recommendation system increases users' intention to purchase and reduces the search time.

• Proceedings of the Korea Database Society Conference
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• 2008.05a
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• pp.211-224
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• 2008

As a lot of information and media are given to users in Internet space nowadays, users feel disoriented or "lost in space" intensively. So it is suggested that we have the system to reduce information overload and to propose effective and efficient information. In this study we present a visualizing technique which uses fisheye views on data adjacency to combine global context and local details for presentation of many results in limited space. Data Adjacency on graph theory is applied to set up degree of interest which is main focus in fisheye views. Graph theory is useful to solve the problem resulted from various combinational optimization, especially it has advantages to analyze issues in information space like Internet. To test the usability of the proposed visualization technique, we compared the effectiveness of different visualization techniques. Results show that our method is evaluated with respect to less time and high satisfaction for a task accomplishment.

• Korean Journal of Computational Design and Engineering
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• v.4 no.2
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• pp.121-126
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• 1999

Existing data structures for non-manifold solid modelers use basic dat entities, such as vertex, edge, loop, face, shell, and region to find adjacency relationships. But, no one clearly identified what additional types of data entitles are necessary to represent incidence relationships. In this paper, we classified the boundary information of vertex, edge, face , and region from the 3-D space view. As the results we can clearly define the boundary information required for adjacency relationships. The existing B-rep data structures for solid modeler are compared whether they have the required boundary information.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3729-3749
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• 2021

At present, deep convolution network-based salient object detection (SOD) has achieved impressive performance. However, it is still a challenging problem to make full use of the multi-scale information of the extracted features and which appropriate feature fusion method is adopted to process feature mapping. In this paper, we propose a new adjacency auxiliary network (AANet) based on multi-scale feature fusion for SOD. Firstly, we design the parallel connection feature enhancement module (PFEM) for each layer of feature extraction, which improves the feature density by connecting different dilated convolution branches in parallel, and add channel attention flow to fully extract the context information of features. Then the adjacent layer features with close degree of abstraction but different characteristic properties are fused through the adjacent auxiliary module (AAM) to eliminate the ambiguity and noise of the features. Besides, in order to refine the features effectively to get more accurate object boundaries, we design adjacency decoder (AAM_D) based on adjacency auxiliary module (AAM), which concatenates the features of adjacent layers, extracts their spatial attention, and then combines them with the output of AAM. The outputs of AAM_D features with semantic information and spatial detail obtained from each feature are used as salient prediction maps for multi-level feature joint supervising. Experiment results on six benchmark SOD datasets demonstrate that the proposed method outperforms similar previous methods.

• The KIPS Transactions:PartB
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• v.12B no.1 s.97
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• pp.31-38
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• 2005

This paper proposes an object-based image retrieval scheme using color adjacency and clustering method. Color adjacency features in boundary regions are utilized to extract candidate blocks of interest from image database and a clustering method is used to extract the regions of interest(ROI) from candidate blocks of interest. To measure the similarity between the query and database images, the histogram intersection technique is used. The color pair information used in the proposed method is robust against translation, rotation, and scaling. Consequently, experimental results have shown that the proposed scheme is superior to existing methods in terms of ANMRR.

• The Transactions of the Korea Information Processing Society
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• v.1 no.1
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• pp.129-139
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• 1994

This paper presents a morphological analysis method for the Korean language. The characteristics and adjacency information of the words can be obtained from sentences in a large corpus. Generally a word can be analyzed to a result by applying the adjacency attributes and rules. However, we have to choose one from the several results for the ambiguous words. The collected morpheme's adjacency attributes and relations with neighbor words are recorded in a well designed dictionaries. With this information, abbreviated words as well as ambiguous words can be almost analyzed successfully. Efficiency of morphological analyzer depends on the information in the dictionaries. A morpheme dictionary and a phrase dictionary have been designed with lexical database, and necessary information extracted from the corpus is stored in the dictionaries.

• Proceedings of the IEEK Conference
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• 2000.06c
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• pp.157-160
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• 2000

This paper proposes a color-based image retrieval method using color adjacency and gradient. In proposed method, both the adjacency of different colors and gradient of a color in homogeneous region are considered as features of an image. The gradient, defined as the maximum distance along the direction with largest change of color, is computed for each pixel to determine whether the center color is similar or different to the neighboring colors. Therefore the problems caused by uniform quantization, which is popularly used at most existing retrieval, can be avoided. And furthermore, the storage of the feature is reduced by the proposed binary representation.