Kamran Paynabar
Kamran Paynabar
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Cited by
Image-based process monitoring using low-rank tensor decomposition
H Yan, K Paynabar, J Shi
IEEE Transactions on Automation Science and Engineering 12 (1), 216-227, 2014
Feature selection for manufacturing process monitoring using cross-validation
C Shao, K Paynabar, TH Kim, JJ Jin, SJ Hu, JP Spicer, H Wang, JA Abell
Journal of Manufacturing Systems 32 (4), 550-555, 2013
An overview and perspective on social network monitoring
WH Woodall, MJ Zhao, K Paynabar, R Sparks, JD Wilson
IISE Transactions 49 (3), 354-365, 2017
Analysis of multichannel nonlinear profiles using uncorrelated multilinear principal component analysis with applications in fault detection and diagnosis
K Paynabar, J Jin, M Pacella
IIE Transactions 45 (11), 1235-1247, 2013
A change-point approach for phase-I analysis in multivariate profile monitoring and diagnosis
K Paynabar, C Zou, P Qiu
Technometrics 58 (2), 191-204, 2016
Characterization of non-linear profiles variations using mixed-effect models and wavelets
K Paynabar, J Jin
Iie transactions 43 (4), 275-290, 2011
Anomaly detection in images with smooth background via smooth-sparse decomposition
H Yan, K Paynabar, J Shi
Technometrics 59 (1), 102-114, 2017
Phase I risk-adjusted control charts for monitoring surgical performance by considering categorical covariates
K Paynabar, J Jin, AB Yeh
Journal of Quality Technology 44 (1), 39-53, 2012
Monitoring temporal homogeneity in attributed network streams
B Azarnoush, K Paynabar, J Bekki, G Runger
Journal of Quality Technology 48 (1), 28-43, 2016
Real-time monitoring of high-dimensional functional data streams via spatio-temporal smooth sparse decomposition
H Yan, K Paynabar, J Shi
Technometrics 60 (2), 181-197, 2018
Multistream sensor fusion-based prognostics model for systems with single failure modes
X Fang, K Paynabar, N Gebraeel
Reliability Engineering & System Safety 159, 322-331, 2017
Identifying the period of a step change in high‐yield processes
R Noorossana, A Saghaei, K Paynabar, S Abdi
Quality and Reliability Engineering International 25 (7), 875-883, 2009
Repeatability of cerebral perfusion using dynamic susceptibility contrast MRI in glioblastoma patients
K Jafari-Khouzani, KE Emblem, J Kalpathy-Cramer, A Bjørnerud, ...
Translational oncology 8 (3), 137-146, 2015
Scalable prognostic models for large-scale condition monitoring applications
X Fang, NZ Gebraeel, K Paynabar
IISE Transactions 49 (7), 698-710, 2017
On the conditional decision procedure for high yield processes
R Noorossana, A Saghaei, K Paynabar, Y Samimi
Computers & Industrial Engineering 53 (3), 469-477, 2007
Multiscale monitoring of autocorrelated processes using wavelets analysis
H Guo, K Paynabar, J Jin
IIE Transactions 44 (4), 312-326, 2012
Multiple tensor-on-tensor regression: An approach for modeling processes with heterogeneous sources of data
MR Gahrooei, H Yan, K Paynabar, J Shi
Technometrics 63 (2), 147-159, 2021
Fast wavenumber measurement for accurate and automatic location and quantification of defect in composite
O Mesnil, H Yan, M Ruzzene, K Paynabar, J Shi
Structural Health Monitoring 15 (2), 223-234, 2016
Dataset: rare event classification in multivariate time series
C Ranjan, M Reddy, M Mustonen, K Paynabar, K Pourak
arXiv preprint arXiv:1809.10717, 2018
Change detection in a dynamic stream of attributed networks
MR Gahrooei, K Paynabar
Journal of Quality Technology 50 (4), 418-430, 2018
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