• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.11a
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• pp.49-52
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• 2014

본 논문에서는 비문(鼻紋)을 이용한 개의 개체인식 시스템을 제안하고자 한다. 기존의 비문을 기반으로 한신원 확인 시스템에서는 종이에 비문을 찍어내어 일반화(generalization)된 데이터를 만드는 과정을 거치거나, 기계학습을 위해 한 개체에 대한 여러 장의 사진을 요구하는 문제점을 가지고 있다. 본 논문에서는 한 개체에 대한 두 장의 사진과 SURF(Speeded-Up Robust Features) 알고리듬을 이용한 특징점 추출(feature detection), FREAK(Fast Retina Keypoint) 특징 기술자(feature descriptor)를 사용한 개체인식 시스템을 제안한다. 비문 이미지에는 개 코의 특성상 반사로 인한 다수의 노이즈가 생기게 되는데 이를 극복하기 위한 전처리 과정이 제안 알고리듬에 포함되어 있다. 실험결과 두 장의 사진으로도 비문 기반의 개체인식을 할 수 있다는 것을 알 수 있다.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.7
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• pp.453-457
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• 2005

With the expansion of Internet, a variety of image databases are widely used and it is needed to select the part of an image what he wants. In contents-based image retrieval system, Zernikie moment and ART Descriptors are used fur shape descriptors in MPEC-7. This paper presents a fast computation method to determine the radius of a bounding circle that encloses an object in a binary image. With conventional methods, the whole area of the image should be scanned first and the distance from every pixel to the center point be computed. The proposed 4-directional scan method and fast circle-drawing algorithm is utilized to minimize the scanning area and reduce the number of operations fur computing the distance. Experimental results show that proposed method saves the computation time to determine the radius of a bounding circle efficiently.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.118-120
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• 2005

본 논문은 모양 특성을 이용한 효과적인 식물 잎 이미지 검색 시스템을 제시한다. 잎 이미지의 더 효과적인 표현을 위해 개선된 MPP 알고리즘을 제안하고, 매칭에 소요되는 시간을 줄이기 위해 기존의 Nearest Neighbor(NN) 검색을 수정한 동적인 매칭 알고리즘을 제시한다. 특히, 더 나은 정확율과 효율성을 위해, 잎 모양과 잎차례를 스케치하여 질의할 수 있도록 하였다. 실험에서는 제안한 알고리즘과 기존의 알고리즘인 Fourier Descriptor, Moment Invariants, MPP와 비교하였다. 1000여개의 식물 잎 이미지를 통한 실험결과는 제안한 방법이 기존의 기법보다 더 좋은 성능임을 보였다.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.2
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• pp.19-28
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• 2019

The purpose of this study is to examine the trends on machine learning and deep learning research in the published journals from the Web of Science Database. To achieve the study purpose, we used the abstracts of 20,664 articles published between 1990 and 2017, which include the word 'machine learning', 'deep learning', and 'artificial neural network' in their titles. Twenty major research topics were identified from topic modeling analysis and they were inclusive of classification accuracy, machine learning, optimization problem, time series model, temperature flow, engine variable, neuron layer, spectrum sample, image feature, strength property, extreme machine learning, control system, energy power, cancer patient, descriptor compound, fault diagnosis, soil map, concentration removal, protein gene, and job problem. The analysis of the time-series linear regression showed that all identified topics in machine learning research were 'hot' ones.

• Journal of the Semiconductor & Display Technology
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• v.16 no.2
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• pp.70-74
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• 2017

Given two stereo images of a scene, it is possible to recover a 3D understanding of the scene. This is the primary way that the human visual system estimates depth. This process is useful in applications like robotics, where depth sensors may be expensive but a pair of cameras is relatively cheap. In this work, we combined our interests to implement a graph cut algorithm for stereo correspondence, and performed evaluation against a baseline algorithm using normalized cross correlation across a variety of metrics. Experimental trials revealed that the proposed descriptor exhibited a significant improvement, compared to the other existing methods.

• Journal of Digital Contents Society
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• v.19 no.6
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• pp.1197-1205
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• 2018

In this paper, we perform Single Image Super Resolution(SISR) for acquired images of EOTS or IRST from naval combat system. In order to conduct super resolution, we use Generative Adversarial Networks(GANs), which consists of a generative model to create a super-resolution image from the given low-resolution image and a discriminative model to determine whether the generated super-resolution image is qualified as a high-resolution image by adjusting various learning parameters. The learning parameters consist of a crop size of input image, the depth of sub-pixel layer, and the types of training images. Regarding evaluation method, we apply not only general image quality metrics, but feature descriptor methods. As a result, a larger crop size, a deeper sub-pixel layer, and high-resolution training images yield good performance.

• Journal of Information Processing Systems
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• v.12 no.1
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• pp.46-56
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• 2016

Dynamic textures are videos that exhibit a stationary property with respect to time (i.e., they have patterns that repeat themselves over a large number of frames). These patterns can easily be tracked by a linear dynamic system. In this paper, a model that identifies the underlying linear dynamic system using wavelet coefficients, rather than a raw sequence, is proposed. Content based threshold filtering based on Set Partitioning in a Hierarchical Tree (SPIHT) helps to get another representation of the same frames that only have low frequency components. The main idea of this paper is to apply SPIHT based threshold filtering on different bands of wavelet transform so as to have more significant information in fewer parameters for singular value decomposition (SVD). In this case, more flexibility is given for the component selection, as SVD is independently applied to the different bands of frames of a dynamic texture. To minimize the time complexity, the proposed model is implemented on a graphics processing unit (GPU). Test results show that the proposed dynamic system, along with a discrete wavelet and SPIHT, achieve a highly compact model with better visual quality, than the available LDS, Fourier descriptor model, and higher-order SVD (HOSVD).

• The KIPS Transactions:PartB
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• v.17B no.2
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• pp.99-106
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• 2010

In this paper, we propose the construction of multi-queries and consistency principle for the user's emotion-based music retrieval system. The features used in the system are MPEG-7 audio descriptors, which are international standards recommended for content-based audio retrievals. In addition we propose the method to determine the weight that represent the importance of each descriptor for each emotion in order to reduce the computation. Also, the proposed retrieval algorithm that uses the relevance feedback based on consistency principal and multi-queries improves the success ratio of musics corresponding to user's emotion.

• Journal of Information Management
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• v.26 no.2
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• pp.61-79
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• 1995

The purpose of this paper is to investigate search efficiency of controlled vocabulary versus uncontrolled vocabulary subject access in online catalog systems. The question of the effectiveness of controlled versus uncontrolled vocabulary in information retrieval has been raised in many literatures. A debate continues in the Library and Information Science Professions over the relative merit, appropriateness, and efficiency of uncontrolled vocabulary subject access in online catalog systems. Actually users used to combine uncontrolled vocabulary subject searching with controlled vocabulary subject searching. But the success of user's subject search depends on his choice of search terms. Also the technical developments that facilitate cooperation among information services in general make it increasingly possible for such cooperation to take place on an international level. In this study, several common types of vocabularies on online catalog systems are described and compared, especially usages of vocabularies in multilingual environment are analyzed.

• Journal of KIISE:Computing Practices and Letters
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• v.7 no.4
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• pp.309-316
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• 2001

MPEG-4 describes audiovisual scenes that are composed of several media objects, organized in a hierarchical fashion. And for end users, it brings higher levels of interaction with content, within the limits set by the author. These spatio-temporal arrangements of the objects in the scene are specified using a parametric methodology, BIFS(BInary Format for Scenes). This paper proposes MPEG-4 Contents Authoring System that provides visual configuration of an MPEG-4 scene and its event information. The developed MPEG-4 Contents Authoring System generates streaming MPEG-4 Contents, such as BIFS stream, OD(Object Descriptor) stream automatically.