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ORCIDUwe Krüger 0001
Person information
- affiliation: Rensselaer Polytechnic Institute, Troy, NY, USA
- affiliation (2012 - 2014): Sultan Qaboos University, Muscat, Oman
- affiliation (2007 - 2012): Petroleum Institute, Abu Dhabi, UAE
- affiliation (2001 - 2007): Queen's University Belfast, UK
- affiliation (PhD 2000): University of Manchester, UK
Other persons with the same name
- Uwe Krüger 0002 — Friedrich Schiller University of Jena, Germany
- Uwe Krüger 0003 — University of Karlsruhe, Germany
- Uwe Krüger 0004 — Goethe University Frankfurt, Germany
- Uwe Krüger 0005 — Uniper Kraftwerke GmbH, Wilhelmshaven, Germany
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2020 – today
- 2022
[i7]Erim Yanik, Uwe Krüger, Xavier Intes, Rahul Rahul, Suvranu De:
Video-based Formative and Summative Assessment of Surgical Tasks using Deep Learning. CoRR abs/2203.09589 (2022)- 2021
- [j29]Xi Fang
, Uwe Kruger, Fatemeh Homayounieh, Hanqing Chao, Jiajin Zhang, Subba R. Digumarthy, Chiara Daniela Arru, Mannudeep K. Kalra, Pingkun Yan:
Association of AI quantified COVID-19 chest CT and patient outcome. Int. J. Comput. Assist. Radiol. Surg. 16(3): 435-445 (2021) - [j28]Yuanyuan Gao, Pingkun Yan, Uwe Kruger, Lora Cavuoto, Steven D. Schwaitzberg, Suvranu De, Xavier Intes:
Functional Brain Imaging Reliably Predicts Bimanual Motor Skill Performance in a Standardized Surgical Task. IEEE Trans. Biomed. Eng. 68(7): 2058-2066 (2021) - [j27]Yiqun Liu, Yiwei He, Shumao Li, Zhenghui Dong, Junping Zhang, Uwe Kruger:
An Auto-Adjustable and Time-Consistent Model for Determining Coagulant Dosage Based on Operators' Experience. IEEE Trans. Syst. Man Cybern. Syst. 51(9): 5614-5625 (2021) - [i6]Erim Yanik, Xavier Intes, Uwe Kruger, Pingkun Yan, David Miller, Brian Van Voorst, Basiel Makled, Jack Norfleet, Suvranu De:
Deep Neural Networks for the Assessment of Surgical Skills: A Systematic Review. CoRR abs/2103.05113 (2021) - 2020
- [j26]Jochen Einbeck, Zakiah I. Kalantan, Uwe Kruger:
Practical Considerations on Nonparametric Methods for Estimating Intrinsic Dimensions of Nonlinear Data Structures. Int. J. Pattern Recognit. Artif. Intell. 34(9): 2058010:1-2058010:35 (2020) - [j25]Grant Haskins, Uwe Kruger, Pingkun Yan:
Deep learning in medical image registration: a survey. Mach. Vis. Appl. 31(1-2): 8 (2020) - [j24]Hengtao Guo, Uwe Kruger, Ge Wang, Mannudeep K. Kalra, Pingkun Yan:
Knowledge-Based Analysis for Mortality Prediction From CT Images. IEEE J. Biomed. Health Informatics 24(2): 457-464 (2020) - [j23]Christopher Wiedeman, Ge Wang, Uwe Kruger:
Modeling of moral decisions with deep learning. Vis. Comput. Ind. Biomed. Art 3: 27 (2020)
2010 – 2019
- 2019
- [j22]Grant Haskins, Jochen Kruecker, Uwe Kruger, Sheng Xu, Peter A. Pinto, Bradford J. Wood, Pingkun Yan:
Learning deep similarity metric for 3D MR-TRUS image registration. Int. J. Comput. Assist. Radiol. Surg. 14(3): 417-425 (2019) - [j21]Hongming Shan, Atul Padole, Fatemeh Homayounieh, Uwe Kruger, Ruhani Doda Khera, Chayanin Nitiwarangkul, Mannudeep K. Kalra, Ge Wang:
Competitive performance of a modularized deep neural network compared to commercial algorithms for low-dose CT image reconstruction. Nat. Mach. Intell. 1(6): 269-276 (2019) - [j20]Hongming Shan, Junping Zhang, Uwe Kruger:
Framework of Randomized Distribution Features for Visual Representation and Categorization. IEEE Trans. Cybern. 49(9): 3599-3606 (2019) - [i5]Hengtao Guo, Uwe Kruger, Ge Wang, Mannudeep K. Kalra, Pingkun Yan:
Knowledge-based Analysis for Mortality Prediction from CT Images. CoRR abs/1902.07687 (2019) - [i4]Grant Haskins, Uwe Kruger, Pingkun Yan:
Deep Learning in Medical Image Registration: A Survey. CoRR abs/1903.02026 (2019) - 2018
- [j19]Hongming Shan, Yi Zhang, Qingsong Yang, Uwe Kruger, Mannudeep K. Kalra, Ling Sun, Wenxiang Cong, Ge Wang:
3-D Convolutional Encoder-Decoder Network for Low-Dose CT via Transfer Learning From a 2-D Trained Network. IEEE Trans. Medical Imaging 37(6): 1522-1534 (2018) - [j18]Hongming Shan, Yi Zhang, Qingsong Yang, Uwe Kruger, Mannudeep K. Kalra, Ling Sun, Wenxiang Cong, Ge Wang:
Correction for "3D Convolutional Encoder-Decoder Network for Low-Dose CT via Transfer Learning From a 2D Trained Network". IEEE Trans. Medical Imaging 37(12): 2750 (2018) - [i3]Hongming Shan, Yi Zhang, Qingsong Yang, Uwe Kruger, Wenxiang Cong, Ge Wang:
3D Convolutional Encoder-Decoder Network for Low-Dose CT via Transfer Learning from a 2D Trained Network. CoRR abs/1802.05656 (2018) - [i2]Grant Haskins, Jochen Kruecker, Uwe Kruger, Sheng Xu, Peter A. Pinto, Bradford J. Wood, Pingkun Yan:
Learning Deep Similarity Metric for 3D MR-TRUS Registration. CoRR abs/1806.04548 (2018) - [i1]Hongming Shan, Atul Padole, Fatemeh Homayounieh, Uwe Krüger, Ruhani Doda Khera, Chayanin Nitiwarangkul, Mannudeep K. Kalra, Ge Wang:
Can Deep Learning Outperform Modern Commercial CT Image Reconstruction Methods? CoRR abs/1811.03691 (2018) - 2017
- [j17]Daniel Howsmon, Uwe Kruger, Stepan Melnyk, S. Jill James, Juergen Hahn:
Classification and adaptive behavior prediction of children with autism spectrum disorder based upon multivariate data analysis of markers of oxidative stress and DNA methylation. PLoS Comput. Biol. 13(3) (2017) - 2016
- [j16]Hongming Shan, Junping Zhang, Uwe Krüger:
Learning Linear Representation of Space Partitioning Trees Based on Unsupervised Kernel Dimension Reduction. IEEE Trans. Cybern. 46(12): 3427-3438 (2016) - 2015
- [j15]Yujie Lin, Uwe Krüger, Junping Zhang, Qi Wang, Lisa Ann Lamont, Lana El Chaar:
Seasonal Analysis and Prediction of Wind Energy Using Random Forests and ARX Model Structures. IEEE Trans. Control. Syst. Technol. 23(5): 1994-2002 (2015) - [j14]Wei Xia, Junping Zhang, Uwe Krüger:
Semisupervised Pedestrian Counting With Temporal and Spatial Consistencies. IEEE Trans. Intell. Transp. Syst. 16(4): 1705-1715 (2015) - [j13]Zhe Li, Uwe Kruger, Lei Xie, Ali Almansoori, Hongye Su:
Adaptive KPCA Modeling of Nonlinear Systems. IEEE Trans. Signal Process. 63(9): 2364-2376 (2015) - 2014
- [j12]Jiusun Zeng, Uwe Kruger, Jaap Geluk, Xun Wang, Lei Xie:
Detecting abnormal situations using the Kullback-Leibler divergence. Autom. 50(11): 2777-2786 (2014) - 2013
- [c12]Jiusun Zeng, Lei Xie, Uwe Krüger, Jie Yu, Jingjing Sha, Xuyi Fu:
Process monitoring based on Kullback Leibler divergence. ECC 2013: 416-421 - [c11]Billy Chang, Uwe Krüger, Rafal Kustra, Junping Zhang:
Canonical Correlation Analysis based on Hilbert-Schmidt Independence Criterion and Centered Kernel Target Alignment. ICML (2) 2013: 316-324 - 2011
- [j11]Junping Zhang, Xiaodan Wang, Uwe Krüger, Fei-Yue Wang:
Principal Curve Algorithms for Partitioning High-Dimensional Data Spaces. IEEE Trans. Neural Networks 22(3): 367-380 (2011) - 2010
- [j10]Junping Zhang, Uwe Krüger, Xiaodan Wang, Dewang Chen:
A Riemannian Distance Approach for Constructing Principal Curves. Int. J. Neural Syst. 20(3): 209-218 (2010)
2000 – 2009
- 2008
- [j9]David Antory, George W. Irwin, Uwe Kruger, Geoffrey McCullough:
Improved process monitoring using nonlinear principal component models. Int. J. Intell. Syst. 23(5): 520-544 (2008) - [j8]Xun Wang, Uwe Kruger, George W. Irwin, Geoffrey McCullough, Neil McDowell:
Nonlinear PCA With the Local Approach for Diesel Engine Fault Detection and Diagnosis. IEEE Trans. Control. Syst. Technol. 16(1): 122-129 (2008) - [j7]Junping Zhang, Dewang Chen, Uwe Krüger:
Adaptive Constraint K-Segment Principal Curves for Intelligent Transportation Systems. IEEE Trans. Intell. Transp. Syst. 9(4): 666-677 (2008) - 2007
- [j6]Uwe Kruger, Sukhbinder Kumar, Tim Littler:
Improved principal component monitoring using the local approach. Autom. 43(9): 1532-1542 (2007) - [c10]Alison McArdle, Uwe Kruger, Tim Littler, Juergen Hahn:
Analysis of IL6 Signal Transduction Model using Reduced Rank Regression. CCA 2007: 670-675 - 2006
- [j5]Dirk Lieftucht, Uwe Kruger, George W. Irwin:
Improved reliability in diagnosing faults using multivariate statistics. Comput. Chem. Eng. 30(5): 901-912 (2006) - [j4]Pingkang Li, Uwe Kruger, George W. Irwin:
Identification of dynamic systems under closed-loop control. Int. J. Syst. Sci. 37(3): 181-195 (2006) - [c9]Srinivasan Rajaraman, Uwe Kruger, M. Sam Mannan, Juergen Hahn:
A New Sensor Fault Diagnosis Technique Based Upon Subspace Identification and Residual Filtering. ICIC (2) 2006: 990-998 - [c8]David Antory, Uwe Kruger, Tim Littler:
A New Principal Curve Algorithm for Nonlinear Principal Component Analysis. ICIC (1) 2006: 1235-1246 - [c7]Lei Xie, Uwe Kruger:
Statistical Processes Monitoring Based on Improved ICA and SVDD. ICIC (1) 2006: 1247-1256 - 2005
- [j3]Uwe Kruger, David Antory, Juergen Hahn, George W. Irwin, Geoffrey McCullough:
Introduction of a nonlinearity measure for principal component models. Comput. Chem. Eng. 29(11-12): 2355-2362 (2005) - [j2]Pingkang Li, George W. Irwin, Uwe Kruger:
A recursive rule base adjustment algorithm for a fuzzy logic controller. Fuzzy Sets Syst. 156(2): 267-284 (2005) - [j1]Qian Chen, Uwe Kruger:
Analysis of extended partial least squares for monitoring large-scale processes. IEEE Trans. Control. Syst. Technol. 13(5): 807-813 (2005) - [c6]Dirk Lieftucht, Uwe Kruger, George W. Irwin:
Compensation terms to improve fault detection in multivariate auto-correlated processes. CDC/ECC 2005: 3827-3831 - [c5]Pingkang Li, Richard J. Treasure, Uwe Kruger:
Dynamic Principal Component Analysis Using Subspace Model Identification. ICIC (1) 2005: 727-736 - 2004
- [c4]Dirk Lieftucht, Uwe Krüger, George W. Irwin:
Improved diagnosis of sensor faults using multivariate statistics. ACC 2004: 4403-4407 - 2001
- [c3]Xun Wang, Uwe Krüger, Barry Lennox, Peter R. Goulding:
A novel multiblock method using latent variable partial least squares. ACC 2001: 3136-3141 - [c2]Uwe Kruger, X. Wang, Q. Chen, S. Joe Qin:
An alternative PLS algorithm for the monitoring of industrial process. ACC 2001: 4455-4459 - 2000
- [c1]Q. Chen, D. Sandoz, R. J. Wynne, Uwe Kruger:
Improved kernel density estimation for clustered data using regularisation and deconvolution. ACC 2000: 1410-1414
Coauthor Index
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