• 전자통신동향분석
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• 제36권2호
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• pp.65-74
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• 2021

In this paper, we discussed the necessity and importance of introducing feature stores to establish a collaborative environment between data engineering work and data science work. We examined the technology trends of feature stores by analyzing the status of some major feature stores. Moreover, by introducing a feature store, we can reduce the cost of performing artificial intelligence (AI) projects and improve the performance and reliability of AI models and the convenience of model operation. The future task is to establish technical requirements for establishing a collaborative environment between data engineering work and data science work and develop a solution for providing a collaborative environment based on this.

• 한국정밀공학회지
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• 제12권11호
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• pp.148-158
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• 1995

This paper describes a hierarchical structure for feature definition and classification, and feature representation method based on frame structure for process planning of prismatic machined components of injection mold. The concept of Volume Removal Directions and Vertical Faces is proposed to develop a method to define and to classify features for components of injection mold systematically. A method for classifying features by the combination of volume removal directions and vertical faces is developed, and also a feature representation method by using frame structure to represent design and manufacturing information is presented.

• 한국CDE학회논문집
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• 제1권2호
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• pp.122-132
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• 1996

Features are generic shapes with which engineers associate certain attributes and knowledge useful in reasoning about the product. Feature-based modeling systems support additional levels of information beyond those available in geometric modelers. The objective of this study is to develop a PC level feature-based modeling system which explicitly represents dimensions of the part. The feature-based modeler retains all the benefits of traditional B-rep. solid models, and represents the dimensions at a high level of a abstraction so that dimension driven geometry can be achieved.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1999년도 하계종합학술대회 논문집
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• pp.643-646
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• 1999

In this paper, we propose a feature extraction method based on Bhattacharyya distance for multiclass problems. The Bhattacharyya distance provides a valuable information in determining the effectiveness of a feature set and has been used as separability measure for feature selection. Recently, a feature extraction algorithm hat been proposed for two normally distributed classes based on Bhattacharyya distance. In this paper, we propose to expand the previous approach to multiclass cases. Experiment results show that the proposed method compares favorably with the conventional methods.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1994년도 추계학술대회 논문집
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• pp.737-742
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• 1994

In this paper , we propose an incremental approach for recognizing a class of machining features from a featurebased design model as a part design proceeds, utilizing various information such as nominal geometry, design intents, and design feature characteristics. The proposed apptroach can handle complex intersecting features and protrusion features designed on oblique faces. The class of recognized volumetric machining features can be expressed as Material Removal Shape Element Volumes (MRSEVs), a PDES/STEP-based library of machining features.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 하계종합학술대회 논문집(4)
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• pp.61-64
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• 2002

In this paper, we propose the iris feature extraction by using statistical methods. There are many approaches for iris feature extraction, but most of them require a set of parameters that one should choose for the transformation to obtain a useful representation of the iris. It would be most useful to estimate the method of the iris feature extraction from iris itself. Therefore, we apply the unsupervised statistical methods for the iris feature extraction.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.1111-1113
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• 2003

In this paper, we investigated a method for feature - based classification to develop software which is suitable to the classification of high resolution satellite imagery . So, we developed related algorithm and designed user interfaces of convenience, considering various elements require for the feature - based classification. The software was tested with eCognition software which is unique commercial software for feature - based classification.

• 대한음성학회:학술대회논문집
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• 대한음성학회 2003년도 5월 학술대회지
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• pp.149-152
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• 2003

In this paper, we present a performance comparison of feature parameters and classifiers for speech/music discrimination. Experiments were carried out on six feature parameters and three classifiers. It turns out that three classifiers shows similar performance. The feature set that captures the temporal and spectral structure of the signal yields good performance, while the phone-based feature set shows relatively inferior performance.

• 한국멀티미디어학회:학술대회논문집
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• 한국멀티미디어학회 2002년도 춘계학술발표논문집(상)
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• pp.245-248
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• 2002

OCR 시스템에서 feature는 인식성능에 상당히 중요한 역할을 한다. gradient feature는 현재까지 개발되어진 여러 가지 feature들 중에서 폭넓게 사용되고 있는 것 중의 하나이다. 본 논문에서는 변형이 심한 인쇄체 숫자를 실험대상으로 하고, Kirsch mask를 이용한 방향성을 가지는 edge를 추출하여 신경망의 입력벡터로 사용할 때 압축의 크기에 따른 인식성능의 차이를 비교하고, 최적의 벡터크기를 제안한다.

• 한국정보통신학회논문지
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• 제10권7호
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• pp.1307-1311
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• 2006

본 연구에서는 행렬 분해 (Matrix Factorization)를 이용하여 음성 스펙트럼의 부분적 특정을 나타낼 수 있는 새로운 음성 파라마터를 제안한다. 제안된 파라미터는 행렬내의 모든 원소가 음수가 아니라는 조건에서 행렬분해 과정을 거치게 되고 고차원의 데이터가 효과적으로 축소되어 나타남을 알 수 있다. 차원 축소된 데이터는 입력 데이터의 부분적인 특성을 표현한다. 음성 특징 추출 과정에서 일반적으로 사용되는 멜 필터뱅크 (Mel-Filter Bank)의 출력 을 Non-Negative 행렬 분해(NMF:Non-Negative Matrix Factorization) 알고리즘의 입 력으로 사용하고, 알고리즘을 통해 차원 축소된 데이터를 음성인식기의 입력으로 사용하여 멜 주파수 캡스트럼 계수 (MFCC: Mel Frequency Cepstral Coefficient)의 인식결과와 비교해 보았다. 인식결과를 통하여 일반적으로 음성인식기의 성능평가를 위해 사용되는 MFCC에 비하여 제안된 특정 파라미터가 인식 성능이 뛰어남을 알 수 있었다.