http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
- 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
- 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
RISS 인기검색어
- 검색키워드
- 저자 : Chong-Jin Ong (검색결과 3 건)
- 무료
- 기관 내 무료
- 유료
-
Feature fusions for 2.5D face recognition in Random Maxout Extreme Learning Machine
Chong, Lee Ying,Ong, Thian Song,Teoh, Andrew Beng Jin Elsevier 2019 Applied soft computing Vol.75 No.-
<P><B>Abstract</B></P> <P>Contemporary face recognition system is often based on either 2D (texture) or 3D (texture + shape) face modality. An alternative modality that utilizes range (depth) facial images, namely 2.5D face recognition emerges. In this paper, we propose a 2.5D face descriptor that based on the Regional Covariance Matrix (RCM), a powerful means of feature fusion technique and a novel classifier dubbed Random Maxout Extreme Learning Machine (RMELM). The RCM of interest is constructed based on the Principal Component Analysis (PCA) filters responses of facial texture and/or range image, wherein the PCA filters are learned from a two-layer PCA network. The RMELM is an ELM variant where the activation function is based on the locally linear maxout function, in place of typical global non-linear functions in ELM. Since the RCM is a special case of symmetric positive definite matrix that resides on the Tensor manifold; a gap exists in between RCM and RMELM, which is a vector-based classifier. To bridge the gap, we flatten the manifold by transforming the RCM to a feature vector via a matrix logarithm operator. Experimental results from two public 3D face databases, FRGC v2.0 database and Gavab database, validated our proposed method is promising in 2.5D face recognition.</P> <P><B>Highlights</B></P> <P> <UL> <LI> A learning-based Regional Covariance Matrix (RCM) based on Principal Component Analysis (PCA) is proposed as a feature descriptor for 2.5D face recognition problem. </LI> <LI> PCARCM is demonstrated as an intra-feature (range features) and inter-feature (range and texture features) fusion container. </LI> <LI> Random Maxout Extreme Learning Machine as classifier is proposed to couple with PCARCM on the Tensor Manifold. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>
-
Shock analysis of a new ultrasonic motor subjected to half-sine acceleration pulses
Hou, Xiaoyan,Lee, Heow Pueh,Ong, Chong Jin,Lim, Siak Piang Techno-Press 2016 Advances in computational design Vol.1 No.4
This paper aims to examine the dynamic response of a newly designed ultrasonic motor under half-sine shock impulses. Impact shock was applied to the motor along x, y or z axis respectively with different pulse widths to check the sensitivity of the motor to the shocks in different directions. Finite Element Analysis (FEA) with the ANSYS software was conducted to obtain the relative displacement of a key point of the motor. Numerical results show that the maximum relative displacement is of micro meter level and the maximum stress is five orders smaller than the Young's modulus of the piezo material, which proves the robustness of the motor.
-
Speed Optimization in Automated Microinjection of Zebrafish Embryos
Peter C.Y. Chen,Shengfeng Zhou,Zhe Lu,Joo-Hoo Nam,Hong Luo,RuowenGe,Chong-Jin Ong,Wei Lin 제어·로봇·시스템학회 2015 International Journal of Control, Automation, and Vol.13 No.5
In this paper we formulate an optimization problem in the design of a speed trajectory for the motion of the micropipette during automated microinjection of zebrafish embryos. The objective of this optimization problem is to minimize the deformation sustained by the zebrafish embryo. We subsequently propose a solution to this optimization problem by first constructing a viscoelastic model of the zebrafish embryo, and then synthesizing an optimal speed trajectory based on a class of polynomials. Furthermore, we present results of numerical simulation and experiments that demonstrate the effectiveness of the proposed solution. The statistically meaningful experimental data (generated using a large sample of zebrafish embryos) provide direct evidence on the advantage of such speed optimization in microinjection.
연관 검색어 추천
이 검색어로 많이 본 자료
활용도 높은 자료
