Uwe Krüger

Orcid: 0000-0001-5664-9499

Affiliations:
  • Rensselaer Polytechnic Institute, Troy, NY, USA
  • Sultan Qaboos University, Muscat, Oman (2012 - 2014)
  • Petroleum Institute, Abu Dhabi, UAE (2007 - 2012)
  • Queen's University Belfast, UK (2001 - 2007)
  • University of Manchester, UK (PhD 2000)


According to our database1, Uwe Krüger authored at least 46 papers between 2000 and 2022.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Online presence:

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Bibliography

2022
Video-based Formative and Summative Assessment of Surgical Tasks using Deep Learning.
CoRR, 2022

2021
An Auto-Adjustable and Time-Consistent Model for Determining Coagulant Dosage Based on Operators' Experience.
IEEE Trans. Syst. Man Cybern. Syst., 2021

Functional Brain Imaging Reliably Predicts Bimanual Motor Skill Performance in a Standardized Surgical Task.
IEEE Trans. Biomed. Eng., 2021

Deep Neural Networks for the Assessment of Surgical Skills: A Systematic Review.
CoRR, 2021

Association of AI quantified COVID-19 chest CT and patient outcome.
Int. J. Comput. Assist. Radiol. Surg., 2021

2020
Modeling of moral decisions with deep learning.
Vis. Comput. Ind. Biomed. Art, 2020

Knowledge-Based Analysis for Mortality Prediction From CT Images.
IEEE J. Biomed. Health Informatics, 2020

Deep learning in medical image registration: a survey.
Mach. Vis. Appl., 2020

Practical Considerations on Nonparametric Methods for Estimating Intrinsic Dimensions of Nonlinear Data Structures.
Int. J. Pattern Recognit. Artif. Intell., 2020

2019
Framework of Randomized Distribution Features for Visual Representation and Categorization.
IEEE Trans. Cybern., 2019

Competitive performance of a modularized deep neural network compared to commercial algorithms for low-dose CT image reconstruction.
Nat. Mach. Intell., 2019

Learning deep similarity metric for 3D MR-TRUS image registration.
Int. J. Comput. Assist. Radiol. Surg., 2019

2018
Correction for "3D Convolutional Encoder-Decoder Network for Low-Dose CT via Transfer Learning From a 2D Trained Network".
IEEE Trans. Medical Imaging, 2018

3-D Convolutional Encoder-Decoder Network for Low-Dose CT via Transfer Learning From a 2-D Trained Network.
IEEE Trans. Medical Imaging, 2018

Can Deep Learning Outperform Modern Commercial CT Image Reconstruction Methods?
CoRR, 2018

Learning Deep Similarity Metric for 3D MR-TRUS Registration.
CoRR, 2018

3D Convolutional Encoder-Decoder Network for Low-Dose CT via Transfer Learning from a 2D Trained Network.
CoRR, 2018

2017
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., 2017

2016
Learning Linear Representation of Space Partitioning Trees Based on Unsupervised Kernel Dimension Reduction.
IEEE Trans. Cybern., 2016

2015
Adaptive KPCA Modeling of Nonlinear Systems.
IEEE Trans. Signal Process., 2015

Semisupervised Pedestrian Counting With Temporal and Spatial Consistencies.
IEEE Trans. Intell. Transp. Syst., 2015

Seasonal Analysis and Prediction of Wind Energy Using Random Forests and ARX Model Structures.
IEEE Trans. Control. Syst. Technol., 2015

2014
Detecting abnormal situations using the Kullback-Leibler divergence.
Autom., 2014

2013
Canonical Correlation Analysis based on Hilbert-Schmidt Independence Criterion and Centered Kernel Target Alignment.
Proceedings of the 30th International Conference on Machine Learning, 2013

Process monitoring based on Kullback Leibler divergence.
Proceedings of the 12th European Control Conference, 2013

2011
Principal Curve Algorithms for Partitioning High-Dimensional Data Spaces.
IEEE Trans. Neural Networks, 2011

2010
A Riemannian Distance Approach for Constructing Principal Curves.
Int. J. Neural Syst., 2010

2008
Adaptive Constraint K-Segment Principal Curves for Intelligent Transportation Systems.
IEEE Trans. Intell. Transp. Syst., 2008

Nonlinear PCA With the Local Approach for Diesel Engine Fault Detection and Diagnosis.
IEEE Trans. Control. Syst. Technol., 2008

Improved process monitoring using nonlinear principal component models.
Int. J. Intell. Syst., 2008

2007
Improved principal component monitoring using the local approach.
Autom., 2007

Analysis of IL6 Signal Transduction Model using Reduced Rank Regression.
Proceedings of the IEEE International Conference on Control Applications, 2007

2006
Identification of dynamic systems under closed-loop control.
Int. J. Syst. Sci., 2006

Improved reliability in diagnosing faults using multivariate statistics.
Comput. Chem. Eng., 2006

Statistical Processes Monitoring Based on Improved ICA and SVDD.
Proceedings of the Intelligent Computing, 2006

A New Sensor Fault Diagnosis Technique Based Upon Subspace Identification and Residual Filtering.
Proceedings of the Computational Intelligence, 2006

A New Principal Curve Algorithm for Nonlinear Principal Component Analysis.
Proceedings of the Intelligent Computing, 2006

2005
Analysis of extended partial least squares for monitoring large-scale processes.
IEEE Trans. Control. Syst. Technol., 2005

A recursive rule base adjustment algorithm for a fuzzy logic controller.
Fuzzy Sets Syst., 2005

Introduction of a nonlinearity measure for principal component models.
Comput. Chem. Eng., 2005

Dynamic Principal Component Analysis Using Subspace Model Identification.
Proceedings of the Advances in Intelligent Computing, 2005

Compensation terms to improve fault detection in multivariate auto-correlated processes.
Proceedings of the 44th IEEE IEEE Conference on Decision and Control and 8th European Control Conference Control, 2005

2004
Improved diagnosis of sensor faults using multivariate statistics.
Proceedings of the 2004 American Control Conference, 2004

2001
A novel multiblock method using latent variable partial least squares.
Proceedings of the American Control Conference, 2001

An alternative PLS algorithm for the monitoring of industrial process.
Proceedings of the American Control Conference, 2001

2000
Improved kernel density estimation for clustered data using regularisation and deconvolution.
Proceedings of the American Control Conference, 2000


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