Uwe Kruger
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Developments and applications of nonlinear principal component analysis–a review
U Kruger, J Zhang, L Xie
Principal manifolds for data visualization and dimension reduction, 1-43, 2008
Deep learning in medical image registration: a survey
G Haskins, U Kruger, P Yan
Machine Vision and Applications 31 (1), 8, 2020
3-D convolutional encoder-decoder network for low-dose CT via transfer learning from a 2-D trained network
H Shan, Y Zhang, Q Yang, U Kruger, MK Kalra, L Sun, W Cong, G Wang
IEEE transactions on medical imaging 37 (6), 1522-1534, 2018
Process monitoring approach using fast moving window PCA
X Wang, U Kruger, GW Irwin
Industrial & engineering chemistry research 44 (15), 5691-5702, 2005
Competitive performance of a modularized deep neural network compared to commercial algorithms for low-dose CT image reconstruction
H Shan, A Padole, F Homayounieh, U Kruger, RD Khera, C Nitiwarangkul, ...
Nature Machine Intelligence 1 (6), 269-276, 2019
Moving window kernel PCA for adaptive monitoring of nonlinear processes
X Liu, U Kruger, T Littler, L Xie, S Wang
Chemometrics and intelligent laboratory systems 96 (2), 132-143, 2009
Recursive partial least squares algorithms for monitoring complex industrial processes
X Wang, U Kruger, B Lennox
Control Engineering Practice 11 (6), 613-632, 2003
Statistical monitoring of complex multivatiate processes: with applications in industrial process control
U Kruger, L Xie
John Wiley & Sons, 2012
Learning deep similarity metric for 3D MR–TRUS image registration
G Haskins, J Kruecker, U Kruger, S Xu, PA Pinto, BJ Wood, P Yan
International journal of computer assisted radiology and surgery 14, 417-425, 2019
Detection of incipient tooth defect in helical gears using multivariate statistics
N Baydar, Q Chen, A Ball, U Kruger
Mechanical systems and signal processing 15 (2), 303-321, 2001
Classification and adaptive behavior prediction of children with autism spectrum disorder based upon multivariate data analysis of markers of oxidative stress and DNA methylation
DP Howsmon, U Kruger, S Melnyk, SJ James, J Hahn
PLoS computational biology 13 (3), e1005385, 2017
Cointegration testing method for monitoring nonstationary processes
Q Chen, U Kruger, AYT Leung
Industrial & Engineering Chemistry Research 48 (7), 3533-3543, 2009
Statistical‐based monitoring of multivariate non‐Gaussian systems
X Liu, L Xie, U Kruger, T Littler, S Wang
AIChE journal 54 (9), 2379-2391, 2008
Nonlinear PCA with the local approach for diesel engine fault detection and diagnosis
X Wang, U Kruger, GW Irwin, G McCullough, N McDowell
IEEE Transactions on Control Systems Technology 16 (1), 122-129, 2007
Improved principal component monitoring of large-scale processes
U Kruger, Y Zhou, GW Irwin
Journal of Process Control 14 (8), 879-888, 2004
Diagnosis of process faults in chemical systems using a local partial least squares approach
U Kruger, G Dimitriadis
AIChE Journal 54 (10), 2581-2596, 2008
Detecting abnormal situations using the Kullback–Leibler divergence
J Zeng, U Kruger, J Geluk, X Wang, L Xie
Automatica 50 (11), 2777-2786, 2014
Synthesis of T2 and Q statistics for process monitoring
Q Chen, U Kruger, M Meronk, AYT Leung
Control Engineering Practice 12 (6), 745-755, 2004
Improved principal component monitoring using the local approach
U Kruger, S Kumar, T Littler
Automatica 43 (9), 1532-1542, 2007
Extended PLS approach for enhanced condition monitoring of industrial processes
U Kruger, Q Chen, DJ Sandoz, RC McFarlane
AIChE journal 47 (9), 2076-2091, 2001
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