• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.19-20
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• 2023

본 논문은 손글씨 인식 분야에서 가장 기본적이고 중요한 주제인 손글씨 데이터 세트에 대한 분류 성능을 분석하고 비교하는 것을 목표로 한다. 이를 위해 ResNet-50 모델을 사용하여 MNIST, EMNIST, KMNIST라는 세 가지 대표적인 손글씨 데이터 세트에 대한 분류 작업을 수행한다. 각 데이터 세트의 특징과 도메인, 그리고 데이터 세트 간의 차이와 특징에 대해 다루며, ResNet-50 모델을 학습하고 평가한 분류 성능을 비교하고 결과에 대해 분석한 결과를 제시한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.718-721
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• 2023

이미지 내 글꼴을 파악하는 것은 디자인 자료 제작, 저작권 확인 등 다양한 곳에서 중요한 문제이다. 하지만 이미지 내 한글 글꼴을 자동으로 식별하는 시스템은 아직 존재하지 않으며, 수동으로 한글 글꼴을 파악하는 것은 시간과 정확도 측면에서 매우 비효율적이다. 따라서 본 논문에서는 이미지 내 한글 글꼴을 자동으로 인식하는 시스템을 개발한다. 본 논문에서 개발한 시스템은 크게 두 가지 기법을 사용한다: (1) 한글의 기하학적인 특성을 활용하여 글자 단위로 텍스트를 인식하며, (2) 단어가 아닌 글자 단위로 글꼴을 분류하고 각 글자에 대한 글꼴 분류 결과를 종합하여 최종적인 글꼴 분류 결과를 얻는다. 10가지 한글 글꼴이 나타나는 직접 제작한 이미지를 사용하여 시스템의 성능을 평가한 결과 제안 방법은 비교 방법에 비해 더욱 정확히 한글 글꼴을 분류함을 확인하였다.

• Journal of the Korea Society for Simulation
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• v.15 no.3
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• pp.49-60
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• 2006

We propose a method to use a state transition model so that the sensing object can be distinguished through classification of signal patterns sensed by a sensor array. Focusing on the design of the model that is able to distinguish the sensed object more exactly, we present an idea in which the modeling elements, 'states' and 'transitions' are defined as each same-sized angle intervals into which the angle interval $(-\frac{\pi}{2},\frac{\pi}{2})$ is divided and the angle differences between adjacent signal values on sampling signal value sequence value sequence sensed from the sensor array in the uniform time interval, respectively. In addition we show the usefulness of our model through experiments.

• Journal of Korean Library and Information Science Society
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• v.37 no.2
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• pp.5-23
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• 2006

The KDC is the most widely used classification system in the elementary school libraries of Korea, but it is only published in full edition. This study is to development abridged KDC edition for elementary school libraries as the subject of KDC. In order to do this, the present writer carried out as follows; to analyse the present state of an class in KDC, to analyse a distribution chart of a class in an practical books and to comes up with a plan of abridged KDC edition as the grounding in the foundation of volume a collection of books. The abridged edition for elementary school libraries is a structural hierarchy of the corresponding full edition which it is based, and is intended for general collections of 20,000 titles or less.

• Journal of Information Management
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• v.35 no.3
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• pp.109-123
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• 2004

The problem of semantic interoperability in science and technology information is frequently raised. Well-established classification scheme will be used as a tool to interchange information between different databases without semantic inconsistency. However, there is still a practical barrier due to different classification schemes each database adopts. Accordingly, it is urgent to harmonize or reconcile those classifications with each other. This paper aims to solve semantic inconsistencies occurred when interchanging information between databases having different classification schemes, the Standard National Sci-Tech Classification and the Standard KISTI Classification. For the purpose a conceptual analysis of science and technology are performed and five consistency/inconsistency types are analyzed based on some examples.

• Korean Journal of Plant Taxonomy
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• v.34 no.2
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• pp.119-152
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• 2004

Allium taxa of Korea were taxonomically reviewed, and classified as three subgenera, ten sections, seventeen species, and three varieties. Among these, Korean endemics were recorded as six taxa; A. koreanum, A. taquetii, A. deltoide-fistulosum, A. linearifolium, A. thunbergii var. deltoides, A. thunbergii var. teretafolium. In addition, A. condensatum, A. splendens and A. maximowiczii proved to distribute only in North Korea. Keys to the subgenera, sections, species and infraspecies with descriptions of each taxon were provided.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.22 no.3
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• pp.207-228
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• 2011

The notes of the classification system are to improve the accuracy and consistency of classification by providing useful information on classification numbers and items. Even though, several notes are used in KDC, they are not enough to keep up with rapidly developing and expanding knowledge of nowadays. The purpose of this study is to suggest appropriate types and improvements of the notes in KDC 5th edition. In order to achieve these purposes, transition of notes in KDC was analyzed. Notes of DDC 23rd edition, NDC new 9th edition, and KDC 5th edition were also analyzed. Based upon these comparison and analysis, problem and improvement of notes in KDC were suggested.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.8C
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• pp.1159-1174
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• 2004

In this paper, we present an efficient algorithm for region analysis of business card images acquired in a PDA by using DCT and information pixel density. The proposed method consists of three parts: region segmentation, information region classification, and text region classification. In the region segmentation, an input business card image is partitioned into 8 f8 blocks and the blocks are classified into information and background blocks using the normalized DCT energy in their low frequency bands. The input image is then segmented into information and background regions by region labeling on the classified blocks. In the information region classification, each information region is classified into picture region or text region by using a ratio of the DCT energy of horizontal and vertical edge components to that in low frequency band and a density of information pixels, that are black pixels in its binarized region. In the text region classification, each text region is classified into large character region or small character region by using the density of information pixels and an averaged horizontal and vertical run-lengths of information pixels. Experimental results show that the proposed method yields good performance of region segmentation, information region classification, and text region classification for test images of several types of business cards acquired by a PDA under various surrounding conditions. In addition, the error rates of the proposed region segmentation are about 2.2-10.1% lower than those of the conventional region segmentation methods. It is also shown that the error rates of the proposed information region classification is about 1.7% lower than that of the conventional information region classification method.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.4
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• pp.267-275
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• 2015

Those land cover maps have widely been used in various fields, such as environmental studies, military strategies as well as in decision-makings. This study proposes a method to extract training data, automatically and classify the cover using ingle satellite images and national land cover maps, provided by the Ministry of Environment. For this purpose, as the initial training data, those three were used; the unsupervised classification, the ISODATA, and the existing land cover maps. The class was classified and named automatically using the class information in the existing land cover maps to overcome the difficulty in selecting classification by each class and in naming class by the unsupervised classification; so as achieve difficulty in selecting the training data in supervised classification. The extracted initial training data were utilized as the training data of MLC for the land cover classification of target satellite images, which increase the accuracy of unsupervised classification. Finally, the land cover maps could be extracted from updated training data that has been applied by an iterative method. Also, in order to reduce salt and pepper occurring in the pixel classification method, the MRF was applied in each repeated phase to enhance the accuracy of classification. It was verified quantitatively and visually that the proposed method could effectively generate the land cover maps.

• Journal of the Korea Convergence Society
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• v.12 no.12
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• pp.39-47
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• 2021

The construction of high-quality input features through effective segmentation is essential for increasing the sentence comprehension of a language model. Improving the quality of them directly affects the performance of the downstream task. This paper comparatively studies the segmentation that effectively reflects the linguistic characteristics of Korean regarding word and sentence classification. The segmentation types are defined in four categories: eojeol, morpheme, syllable and subchar, and pre-training is carried out using the RoBERTa model structure. By dividing tasks into a sentence group and a word group, we analyze the tendency within a group and the difference between the groups. By the model with subchar-level segmentation showing higher performance than other strategies by maximal NSMC: +0.62%, KorNLI: +2.38%, KorSTS: +2.41% in sentence classification, and the model with syllable-level showing higher performance at maximum NER: +0.7%, SRL: +0.61% in word classification, the experimental results confirm the effectiveness of those schemes.