• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.05a
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• pp.187-190
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• 2001

Due to the recent proliferation of the internet, it is broadly granted that the necessity of the automatic document categorization has been on the rise. Since it is a heavy time-consuming work and takes too much manpower to process and classify manually, we need a system that categorizes them automatically as their contents. In this paper, we propose the automatic E-mail response system that is based on 2 hierarchical document clustering methods. One is to get the final result from the classifier trained seperatly within each class, after clustering the whole documents into 3 groups so that the first classifier categorize the input documents as the corresponding group. The other method is that the system classifies the most distinct classes first as their similarity, successively. Neural networks have been adopted as classifiers, we have used dendrograms to show the hierarchical aspect of similarities between classes. The comparison among the performances of hierarchical and non-hierarchical classifiers tells us clustering methods have provided the classification efficiency.

• Journal of Korean Neurosurgical Society
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• v.65 no.1
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• pp.107-113
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• 2022

Objective : To describe the surgical management and postoperative outcomes in infants with metopic synostosis. Methods : We conducted a 5 years retrospective chart review of patients who underwent surgical correction of metopic synostosis at two university hospitals in Egypt during the period between June 2014 and June 2019. The study is conducted to 18 children. The type of surgical procedures and postoperative outcomes were assessed in all patients. Results : Five cases (27.8%) underwent endoscopic-assisted suturectomy, 10 cases (55.6%) underwent craniofacial reconstruction, and three cases (16.6%) underwent open burring of the metopic ridge. Fifteen patients underwent one surgery and three patients (16.6%) who need second operation. Ten patients (55.6%) had class I Whitaker classification. Conclusion : Regardless of type of surgery, the outcomes of surgical correction of metopic synostosis are excellent with only a few patients require revision or develop major complications.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.95-97
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• 2022

본 논문에서는 산업 현장에서 발생하는 불량품 탐지 분야에서 효율적으로 생산품의 불량을 탐지할 수 있는 PaDiM 구조의 Backbone 모델을 단일 Wide-ResNet 대신 두 개의 Wide-ResNet을 사용함으로써, 단일 모델에서 추출된 저차원의 Feature를 앙상블을 통해 성능 향상을 일으킬 수 있는 것을 증명하였다. 단일 Wide-ResNet 환경에서는 MVTec 데이터셋에서 생성된 다변량 가우시안 분포가 데이터셋의 적은 샘플수로 인하여 각 클래스 간 불균형이 발생하는 문제를 동종 앙상블을 통해 해결할 수 있었다. 따라서 본 논문에서는 제안하는 동종 모델의 앙상블을 사용함으로써 기존의 One-class classification 환경에서 불량품 탐지환경에서 적은 수의 데이터 샘플 환경에서 성능 향상을 나타낼 수 있음을 입증하였다.

• International Journal of Computer Science & Network Security
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• v.24 no.5
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• pp.129-134
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• 2024

Object Detection is an emerging technology in the field of Computer Vision and Image Processing that deals with detecting objects of a particular class in digital images. It has considered being one of the complicated and challenging tasks in computer vision. Earlier several machine learning-based approaches like SIFT (Scale-invariant feature transform) and HOG (Histogram of oriented gradients) are widely used to classify objects in an image. These approaches use the Support vector machine for classification. The biggest challenges with these approaches are that they are computationally intensive for use in real-time applications, and these methods do not work well with massive datasets. To overcome these challenges, we implemented a Deep Learning based approach Convolutional Neural Network (CNN) in this paper. The Proposed approach provides accurate results in detecting objects in an image by the area of object highlighted in a Bounding Box along with its accuracy.

• Korean Journal of Remote Sensing
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• v.25 no.2
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• pp.145-154
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• 2009

High spatial resolution satellite image classification has a limitation when only using the spectral information due to the complex spatial arrangement of features and spectral heterogeneity within each class. Therefore, the extraction of the spatial information is one of the most important steps in high resolution satellite image classification. This study proposes a new spatial feature extraction method, named SSI(Shape-Size Index). SSI uses a simple region-growing based image segmentation and allocates spatial property value in each segment. The extracted feature is integrated with spectral bands to improve overall classification accuracy. The classification is achieved by applying a SVM(Support Vector Machines) classifier. In order to evaluate the proposed feature extraction method, KOMPSAT-2 and QuickBird-2 data are used for experiments. It is demonstrated that proposed SSI algorithm leads to a notable increase in classification accuracy.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.16 no.1
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• pp.75-84
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• 1998

To achieve more accurate information from satellite image data, a research on a technique for mixed pixel ex-traction has been produced. The mixed pixels with only two land covers have been experimented. By analyzing canonical vector in canonical correlation classification, the mixed pixels have been classified. The ratio of the two canonical weighted values-the elements of canonical vector have been used as a threshold to discriminate mixed pixels. In case of the classification for the mixed pixels of bridge and water class in TM data before or after the 1st of September, the threshold for the optimal classification of the mixed pixels is 4.0. That is, if the ratio of the two canonical weighted values is less than 4.0, the pixel is a mixed pixel. Also, using the distribution of canonical weighted values, the constitution percentages of land covers within one mixed pixel can be approximately deducted. The accuracy of mixed pixel extraction for experimental area is 90％ and quite acceptable. Conclusively, a technique for mixed pixel extraction by canonical vector analysis is effective.

• Journal of the Korea Society of Computer and Information
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• v.12 no.1 s.45
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• pp.51-56
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• 2007

Feature functions were used for the classification of music. The spectral roll-off, variance, average peak level, and class were chosen to make up a feature function vector. Among these, it is the spectral roll-off function that has a low-frequency to high-frequency ratio. To find the optimal roll-off point, the roll-off points from 0.05 to 0.95 were swept. The classification success rate was monitored as the roll-off point was being changed. The data that were used for the experiments were taken from the sounds made by a modern violin and a baroque one. Their shapes and sounds are similar, but they differ slightly in sound texture. As such, the data obtained from the sounds of these two kinds of violin can be useful in finding an adequate roll-off point. The optimal roll-off point, as determined through the experiment, was 0.85. At this point, the classification success rate was 85%, which was the highest.

• The KIPS Transactions:PartB
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• v.16B no.4
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• pp.281-288
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• 2009

This paper proposes a novel algorithm for the efficient classification and annotation of medical images, especially X-ray images. Since X-ray images have a bright foreground against a dark background, we need to extract the different visual descriptors compare with general nature images. In this paper, a Color Structure Descriptor (CSD) based on Harris Corner Detector is only extracted from salient points, and an Edge Histogram Descriptor (EHD) used for a textual feature of image. These two feature vectors are then applied to a multi-class Support Vector Machine (SVM), respectively, to classify images into one of 20 categories. Finally, an image has the Annotation Code Array based on the pre-defined hierarchical relations of categories and priority code order, which is given the several optimal keywords by the Annotation Code Array. Our experiments show that our annotation results have better annotation performance when compared to other method.

• Journal of Korean Neurosurgical Society
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• v.39 no.1
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• pp.16-19
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• 2006

Objective : The purpose of this study is to evaluate the effect of the corpus callosotomy and to elucidate possible prognostic factors. Methods : The cases of 39 patients who underwent corpus callosotomy were reviewed retrospectively. Clinical outcomes were analyzed using Engel's classification, with consideration of various presurgical conditions and the extent of the callosal resection during follow-up more than one year. Results : Satisfactory outcome [Engel's class I, II] was obtained in 20 patients [51%] of 39 patients. In 36 cases with drop attack seizures, the class I, II outcomes were 22 patients [61%]. When the patients were grouped according to the extent of callosal resection, the class I, II outcomes were 50% of the patients with anterior 1/2 or 2/3, 50% of those with anterior 4/5 callosotomy, and 57% of those with total callosotomy, respectively. The mean follow-up period was 34 months [24 to 58 months]. Conclusion : Although it is not statistically significant, the patients who had underwent total callosotomy show better outcomes than those with partial callosotomy. Corpus callosotomy is efficacious in controlling medically intractable epilepsy in appropriately selected patients.

• Journal of KIISE:Information Networking
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• v.31 no.6
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• pp.556-565
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• 2004

A Sandbox has been widely used to prevent damages caused by running of unknown malicious codes. It prevents damages by containing running environment of a program. There is a trade-off in using sandbox, between configurability and ease-of-use. MAPbox, an instance system of sandbox, had employed sandbox classification technique to satisfy both configurability and ease-of-use [1]. However, the configurability of MAPbox can be improved further. In this paper, we introduce a technique to attach dynamic class facility to MAPbox and implement MAPbox-advanced one. Newly generated class in our system has an access control with proper privileges. We show an example for improvements which denote our system have increased the configurability of MAPbox. It was determined as abnormal by MAPbox although is not. Our system could determine it as normal. We also show our techniques to overcome obstacles to implement the system.