Zobrazeno 1 - 10
of 31
pro vyhledávání: '"Lu-Hung Chen"'
Autor:
Ci-Ren Jiang, Wei Chih Cheng, Yuh-Lin Wang, Chi Hung Lin, Lu Hung Chen, Da-Wei Wang, Juen-Kai Wang, Yu Ming Deng, Ruwen Jou
Publikováno v:
Analytical Chemistry. 93:2785-2792
Tuberculosis caused by Mycobacterium tuberculosis complex (MTBC) is one of the major infectious diseases in the world. Identification of MTBC and differential diagnosis of nontuberculous mycobacteria (NTM) species impose challenges because of their t
Autor:
Hao-An Yang, Shu-Min Tsai, Ming-Lin Chuang, Hong-Wei Yan, Yung-Cheng Yao, Guan-Wei Chen, Lu-Hung Chen
Publikováno v:
ICCE-TW
Fish is rich in high-protein, multi-vitamins, low-calorie, and other nutritional value. It is an indispensable delicacy. How to choose fresh fish is a difficult work. Although experts suggest three observation points for choosing fresh fish: 1. Fish
Sensible Functional Linear Discriminant Analysis Effectively Discriminates Enhanced Raman Spectra of
Autor:
Wei-Chih, Cheng, Lu-Hung, Chen, Ci-Ren, Jiang, Yu-Ming, Deng, Da-Wei, Wang, Chi-Hung, Lin, Ruwen, Jou, Juen-Kai, Wang, Yuh-Lin, Wang
Publikováno v:
Analytical chemistry. 93(5)
Tuberculosis caused by
Autor:
Lu-Hung Chen, Ci-Ren Jiang
Publikováno v:
Statistics and Computing. 27:1181-1192
Functional principal component analysis is one of the most commonly employed approaches in functional and longitudinal data analysis and we extend it to analyze functional/longitudinal data observed on a general $d$-dimensional domain. The computatio
Publikováno v:
IEEE BigData
Erasable-itemset mining used in production planning identifies itemsets (or components) that, if removed, would not affect profits. Formally, an itemset is erasable if its gain ratio is equal to or smaller than a given maximum gain-ratio threshold r.
Autor:
Lu-Hung Chen, Ci-Ren Jiang
Fisher’s linear discriminant analysis (LDA) is extended to both densely recorded functional data and sparsely observed longitudinal data for general c -category classification problems. An efficient approach is proposed to identify the optimal LDA
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6aa177da385b81f862a789cf16f9d3ea
http://arxiv.org/abs/1606.03844
http://arxiv.org/abs/1606.03844
Publikováno v:
Journal of the American Statistical Association. 104:1179-1191
Multiparameter likelihood models (MLMs) with multiple covariates have a wide range of applications; however, they encounter the “curse of dimensionality” problem when the dimension of the covariates is large. We develop a generalized multiparamet
Publikováno v:
Journal of Statistical Planning and Inference. 139:236-245
First, we propose a new method for estimating the conditional variance in heteroscedasticity regression models. For heavy tailed innovations, this method is in general more efficient than either of the local linear and local likelihood estimators. Se
Publikováno v:
ICPR
Linear discriminant analysis that takes spatial smoothness into account has been developed and widely used in image processing society. However, two questions remain unanswered. First, which is the best way to incorporate the smoothness property of i
Publikováno v:
ICIP
This paper introduces a general framework for image contrast enhancement based on histogram equalization (HE) and specification (HS). Traditional HE and HS are simple and effective, but they often amplify the noise level of the image while enhancing