• ETRI Journal
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• 제38권2호
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• pp.347-355
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• 2016

In face examinations, gender classification (GC) is one of several fundamental tasks. Recent literature on GC primarily utilizes datasets containing high-resolution images of faces captured in uncontrolled real-world settings. In contrast, there have been few efforts that focus on utilizing low-resolution images of faces in GC. We propose a GC method based on a pixel classifier boosting with modified census transform features. Experiments are conducted using large datasets, such as Labeled Faces in the Wild and The Images of Groups, and standard protocols of GC communities. Experimental results show that, despite using low-resolution facial images that have a 15-pixel inter-ocular distance, the proposed method records a higher classification rate compared to current state-of-the-art GC algorithms.

• 한국윤활학회:학술대회논문집
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• 한국윤활학회 1996년도 제24회 춘계학술대회
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• pp.35-40
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• 1996

Friction and wear behavior of MoS$_{2}$ bonded films were evaluated at a Block-on-Ring typed tribo-tester, and their properties were compared with those of Falex tester in terms of the wear life of the films. Test results showed that friction and wear properties were significantly affected by the test methods of different contact configuration, and the wear life at a Block-on-Ring type tribo-tester was mostly governed by the resin binder. To obtain long wear life of the films, various combinations of solid-resin-content ratio and chemical resin modification were attempted and evaluated. Adhesion properties of resin binders were also measured and compared by using a scratch tester.

• Tribology and Lubricants
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• 제16권3호
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• pp.173-181
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• 2000

Friction, wear and corrosion characteristics of various MoS$_2$ bonded film lubricants were investigated to apply them to automotive wheel joints. MoS$_2$ bonded film lubricants were formulated by combinations of several additives and binders, and they were coated onto the pre-treated surfaces of specimens. Friction and wear characteristics were evaluated with Falex pin & vee-block test and LFW-1 block-on-ring test. For the corrosion resistant characteristics of the films, salt solution spray corrosion tests were performed. Results showed that MoS$_2$ bonded films containing both inorganic and organic corrosion-resistant additives yielded a synergy effect on anti-corrosion resistance. Also, binders having the better water-proof and thermal stability showed the lower friction and higher corrosion resistance.

• Tribology and Lubricants
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• 제13권3호
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• pp.20-27
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• 1997

The tribological behavior for $MoS_2$ bonded films is evaluated according to the international standard testing methods, such as ASTM D 2625 (Falex tester) and ASTM D 2714 (LFW1 tester). It has been well known that the tribological behavior for $MoS_2$ bonded films is affected by several factors. However, in this work, the wear life for $MoS_2$ bonded films is mainly experimentally measured with different contact geometry, and evaluated in terms of the frictional heating according to the contact geometry of tribotester. The test results show that the wear life of $MoS_2$ bonded films is significantly affected not only by the frictional heating, but also by the contact pressure, test running-in conditions, and the contact conformity.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2009년도 추계학술발표대회
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• pp.623-624
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• 2009

본 논문에서는 신경망의 오류 역전파(Backpropagation) 학습 알고리즘을 이용한 얼굴의 정상 비정상을 인식하는 보안 시스템을 제안하였다. 제안된 시스템은 정지영상 및 동영상에서 입력된 얼굴영상을 전처리 단계에서 얼굴영역을 검출하여 $160{\times}160$ 크기의 고정 크기로 확대 및 축소 작업을 거친다. Mosaic 처리와 LaplacianEdge 처리를 거쳐 $40{\times}40$ 크기로 이진화한 정규화 데이터를 Gravity-Center 처리를 한다. 오류 역전파 학습 알고리즘으로 얼굴의 특징을 학습한 후 각종 정상 및 비정상 얼굴 데이터를 이용하여 인식률을 실험 하였다. 실험데이터는 이 분야의 공인 자료인 LFW Face Database[7] 데이터를 사용하였으며, 실험결과는 제안된 방법이 문제 해결에 적합한 접근임을 보여준다.

• 정보과학회 논문지
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• 제41권9호
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• pp.666-673
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• 2014

본 논문에서는 비제약적 얼굴 데이터 베이스를 위한 확장성 있는 얼굴 인식 방법을 연구하고, 간단한 실험 결과를 소개한다. 기존의 얼굴 인식 연구들은 주로 조명, 얼굴 각도, 표정, 배경 등 제약이 있는 환경에서의 정확도 향상에 초점을 맞추고 있어서 비제약적 얼굴 데이터 베이스에 사용하기에 적합하지 않다. 제안하는 얼굴인식 방법은 비제약적 얼굴 인식을 위한 특징 추출 알고리즘으로, 먼저 지역적 특징이 존재하는 눈, 코, 입과 같이 얼굴의 중요한 특징을 나타내는 영역을 분리한다. 각 얼굴 주요 위치는 고차원의 다중 스케일 국부 이진패턴 히스토그램(Multi-scale LBP histogram) 특징 벡터로 기술된다. 단일 얼굴 주요 위치에 해당하는 다중 스케일 국부 이진패턴 히스토그램 특징 벡터는 주성분 분석법(PCA: Principal Component Analysis)과 선형 판별 분석법(LDA: Linear Discriminant Analysis)의 차원 축소 과정을 통해 저차원 얼굴 특징 벡터를 생성한다. 저차원 얼굴 특징 벡터는 랭크 획득과 Precision at k(p@k) 성능 평가 방법을 이용하여 제안한 알고리즘의 얼굴 인식 성능을 검증한다. 본 연구는 FERET, LFW 및 PubFig83 데이터 베이스를 이용하여 얼굴 인식 실험을 수행하였으며, 제안한 알고리즘을 이용한 얼굴 인식 방법이 기존의 방법보다 향상된 인식성능을 보였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권1호
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• pp.368-391
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• 2018

Face recognition (FR) with a single sample per person (SSPP) is common in real-world face recognition applications. In this scenario, it is hard to predict intra-class variations of query samples by gallery samples due to the lack of sufficient training samples. Inspired by the fact that similar faces have similar intra-class variations, we propose a virtual sample generating algorithm called k nearest neighbors based virtual sample generating (kNNVSG) to enrich intra-class variation information for training samples. Furthermore, in order to use the intra-class variation information of the virtual samples generated by kNNVSG algorithm, we propose image set based multimanifold discriminant learning (ISMMDL) algorithm. For ISMMDL algorithm, it learns a projection matrix for each manifold modeled by the local patches of the images of each class, which aims to minimize the margins of intra-manifold and maximize the margins of inter-manifold simultaneously in low-dimensional feature space. Finally, by comprehensively using kNNVSG and ISMMDL algorithms, we propose k nearest neighbor virtual image set based multimanifold discriminant learning (kNNMMDL) approach for single sample face recognition (SSFR) tasks. Experimental results on AR, Multi-PIE and LFW face datasets demonstrate that our approach has promising abilities for SSFR with expression, illumination and disguise variations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권11호
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• pp.5474-5490
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• 2017

Although two-dimensional principal component analysis (2DPCA) has been shown to be successful in face recognition system, it is still very sensitive to illumination variations. To reduce the effect of these variations, texture-based techniques are used due to their robustness to these variations. In this paper, we explore several texture-based techniques and determine the most appropriate one to be used with 2DPCA-based techniques for face recognition. We also propose a new distance metric computation in 2DPCA called Row Assembled Matrix Distance (RowAMD). Experiments on Yale Face Database, Extended Yale Face Database B, AR Database and LFW Database reveal that the proposed RowAMD distance computation method outperforms other conventional distance metrics when Local Line Binary Pattern (LLBP) and Multi-scale Block Local Binary Pattern (MB-LBP) are used for face authentication and face identification, respectively. In addition to this, the results also demonstrate the robustness of the proposed RowAMD with several texture-based techniques.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권6호
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• pp.3144-3164
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• 2019

Face recognition systems have several potential applications, such as security and biometric access control. Ongoing research is focused to develop a robust face recognition algorithm that can mimic the human vision system. Face pose, non-uniform illuminations, and low-resolution are main factors that influence the performance of face recognition algorithms. This paper proposes a novel method to handle the aforementioned aspects. Proposed face recognition algorithm initially uses 68 points to locate a face in the input image and later partially uses the PCA to extract mean image. Meanwhile, the AdaBoost and the LDA are used to extract face features. In final stage, classic nearest centre classifier is used for face classification. Proposed method outperforms recent state-of-the-art face recognition algorithms by producing high recognition rate and yields much lower error rate for a very challenging situation, such as when only frontal ($0^{\circ}$) face sample is available in gallery and seven poses ($0^{\circ}$, ${\pm}30^{\circ}$, ${\pm}35^{\circ}$, and ${\pm}45^{\circ}$) as a probe on the LFW and the CMU Multi-PIE databases.

• Tribology and Lubricants
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• 제39권6호
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• pp.235-243
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• 2023

This paper presents the fabrication process of water-lubricated plastic bearings. Plastic bearings require good mechanical properties and tribological properties as well as elasticity and shock resistance, especially when lubricated in dirty water conditions. In this study, sleeve-type plastic bearings are produced by winding a prepreg sheet, which primary contains nitrile rubber (NBR)-modified epoxy, self-lubricating fillers, and various types of lattice-structured reinforcing fibers such as carbon, Aramid, and polyethylene terephthalate. A thermosetting epoxy is chemically modified with NBR to impart elasticity and low-friction characteristics in water conditions. Experimental investigations are conducted to examine the mechanical and tribological characteristics of the developed bearing materials, and the results are compared with the characteristics of a commercial plastic bearing (Thordon SXL), well known as a water-lubricated bearing. A Thordon bearing (mainly composed of polyurethane) exhibits an extremely low load-bearing capacity and is thus only suitable for medium loading (1~10MPa). The tribological characteristics of the test materials are evaluated through Falex block-on-ring (LFW-1) friction and wear tests. The results indicate that friction exhibited by the carbon-fiber-reinforced NBR-10wt.%-modified epoxy composite material, incorporated with the addition of 20wt.% UHMWPE and 6wt.% paraffin wax, is lower than that of the Thorden bearings, whereas its wear resistance surpass that of Thorden ones. Because of these features, the load carrying capacity of the fabricated composite (>10MPa) is higher than that of the Thorden bearings. These results confirm the applicability of water-lubricated plastic bearing materials developed in this study.