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Tim W. Nattkemper
Person information
- affiliation: Bielefeld University, Center for Biotechnology
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2020 – today
- 2022
- [j36]Konstantinos Tzanakis
, Tim W. Nattkemper
, Karsten Niehaus
, Stefan P. Albaum
:
MetHoS: a platform for large-scale processing, storage and analysis of metabolomics data. BMC Bioinform. 23(1): 267 (2022) - [j35]Mingkun Tan
, Daniel Langenkämper
, Tim W. Nattkemper
:
The Impact of Data Augmentations on Deep Learning-Based Marine Object Classification in Benthic Image Transects. Sensors 22(14): 5383 (2022) - 2021
- [j34]Torben Möller, Tim W. Nattkemper
:
ALMI - A Generic Active Learning System for Computational Object Classification in Marine Observation Images. Sensors 21(4): 1134 (2021) - 2020
- [j33]Martin Zurowietz
, Tim W. Nattkemper
:
Unsupervised Knowledge Transfer for Object Detection in Marine Environmental Monitoring and Exploration. IEEE Access 8: 143558-143568 (2020) - [j32]Martin Zurowietz
, Tim W. Nattkemper
:
An Interactive Visualization for Feature Localization in Deep Neural Networks. Frontiers Artif. Intell. 3: 49 (2020) - [i1]Karsten Wüllems, Tim W. Nattkemper:
SoRC - Evaluation of Computational Molecular Co-Localization Analysis in Mass Spectrometry Images. CoRR abs/2009.14677 (2020)
2010 – 2019
- 2019
- [j31]Georges Hattab
, Tim W. Nattkemper
:
SeeVis - 3D space-time cube rendering for visualization of microfluidics image data. Bioinform. 35(10): 1802-1804 (2019) - [j30]Karsten Wüllems
, Jan Kölling, Hanna Bednarz, Karsten Niehaus, Volkmar H. Hans, Tim W. Nattkemper
:
Detection and visualization of communities in mass spectrometry imaging data. BMC Bioinform. 20(1): 303:1-303:12 (2019) - 2018
- [c39]Daniel Langenkämper, Robin van Kevelaer, Tim W. Nattkemper:
Strategies for Tackling the Class Imbalance Problem in Marine Image Classification. CVAUI/IWCF/MIPPSNA@ICPR 2018: 26-36 - [c38]Torben Möller, Ingunn Nilssen, Tim Wilhelm Nattkemper
:
Tracking Sponge Size and Behaviour with Fixed Underwater Observatories. CVAUI/IWCF/MIPPSNA@ICPR 2018: 45-54 - 2017
- [c37]Ingunn Nilssen, Torben Möller, Tim W. Nattkemper:
Active Learning for the Classification of Species in Underwater Images from a Fixed Observatory. ICCV Workshops 2017: 2891-2897 - 2016
- [j29]Shan-E-Ahmed Raza
, Daniel Langenkämper
, Korsuk Sirinukunwattana
, David B. A. Epstein, Tim W. Nattkemper
, Nasir M. Rajpoot
:
Robust normalization protocols for multiplexed fluorescence bioimage analysis. BioData Min. 9: 11 (2016) - [j28]Benedikt G. Brink
, Annica Seidel, Nils Kleinbölting, Tim W. Nattkemper
, Stefan P. Albaum:
Omics Fusion - A Platform for Integrative Analysis of Omics Data. J. Integr. Bioinform. 13(4) (2016) - [c36]Jonas Osterloff, Ingunn Nilssen, Johanna Jarnegren, Pål Buhl-Mortensen
, Tim W. Nattkemper
:
Polyp Activity Estimation and Monitoring for Cold Water Corals with a Deep Learning Approach. CVAUI@ICPR 2016: 1-6 - [c35]Torben Möller, Ingunn Nilssen, Tim W. Nattkemper:
Data-Driven Long Term Change Analysis in Marine Observatory Image Streams. CVAUI@ICPR 2016: 13-18 - [c34]Daniel Langenkämper, Tim W. Nattkemper:
COATL - a learning architecture for online real-time detection and classification assistance for environmental data. ICPR 2016: 597-602 - [c33]Torben Möller, Ingunn Nilssen, Tim W. Nattkemper
:
Change detection in marine observatory image streams using Bi-Domain Feature Clustering. ICPR 2016: 793-798 - 2014
- [j27]Daniel Langenkämper
, Alexander Goesmann
, Tim W. Nattkemper
:
AKE - the Accelerated k-mer Exploration web-tool for rapid taxonomic classification and visualization. BMC Bioinform. 15: 384 (2014) - [c32]Magnus Rathke, Jan Kölling, Tim W. Nattkemper:
Interactive and dynamic web-based visual exploration of high dimensional bioimages with real time clustering. GCB 2014: 44-53 - [c31]Timm Schoening, Thomas Kuhn, Tim W. Nattkemper
:
Seabed Classification Using a Bag-of-Prototypes Feature Representation. CVAUI@ICPR 2014: 17-24 - [c30]Jonas Osterloff, Timm Schoening, Melanie Bergmann
, Jennifer M. Durden
, Henry A. Ruhl, Tim W. Nattkemper
:
Ranking Color Correction Algorithms Using Cluster Indices. CVAUI@ICPR 2014: 41-48 - [e1]Robert Giegerich, Ralf Hofestädt, Tim W. Nattkemper:
German conference on bioinformatics 2014, September 28 - October 1, 2014, Bielefeld, Germany. LNI P-235, GI 2014, ISBN 978-3-88579-629-9 [contents] - 2013
- [j26]Nikolas Kessler, Heiko Neuweger, Anja Bonte
, Georg Langenkämper
, Karsten Niehaus, Tim W. Nattkemper
, Alexander Goesmann
:
MeltDB 2.0-advances of the metabolomics software system. Bioinform. 29(19): 2452-2459 (2013) - [c29]Claudia Rubiano, Thomas Merkle, Tim W. Nattkemper:
Using a Random Forest Classifier to Find Nuclear Export Signals in Proteins of Arabidopsis thaliana. BIOINFORMATICS 2013: 98-104 - 2012
- [j25]Jan Kölling
, Daniel Langenkämper
, Sylvie Abouna, Michael Khan
, Tim W. Nattkemper
:
WHIDE - a web tool for visual data mining colocation patterns in multivariate bioimages. Bioinform. 28(8): 1143-1150 (2012) - [c28]Tim W. Nattkemper:
Are we Ready for Science 2.0?. KMIS 2012: 302-306 - [c27]Jan Kölling, Magnus Rathke, Dominic Gardner, Tim W. Nattkemper, Sylvie Abouna, Michael Khan:
Analyzing multi-tag bioimages with BioIMAX colocation mining tools. ISBI 2012: 1304-1307 - 2011
- [j24]Christian W. Martin, Anika Tauchen, Anke Becker
, Tim W. Nattkemper
:
A Normalized Tree Index for identification of correlated clinical parameters in microarray experiments. BioData Min. 4: 2 (2011) - [j23]Christian Loyek, Nasir M. Rajpoot
, Michael Khan
, Tim W. Nattkemper
:
BioIMAX: A Web 2.0 approach for easy exploratory and collaborative access to multivariate bioimage data. BMC Bioinform. 12: 297 (2011) - [j22]Christian Loyek, Alexander Bunkowski, Wolfgang Vautz, Tim W. Nattkemper
:
Web2.0 paves new ways for collaborative and exploratory analysis of chemical compounds in spectrometry data. J. Integr. Bioinform. 8(2) (2011) - [j21]Alexandra Scherbart, Tim W. Nattkemper
:
Looking inside self-organizing map ensembles with resampling and negative correlation learning. Neural Networks 24(1): 130-141 (2011) - [j20]Julia Herold, Christian Loyek, Tim W. Nattkemper
:
Multivariate image mining. WIREs Data Mining Knowl. Discov. 1(1): 2-13 (2011) - [c26]Timm Schoening, Volkmar H. Hans, Tim W. Nattkemper
:
Towards Improved Epilepsia Diagnosis by Unsupervised Segmentation of Neuropathology Tissue Sections using Ripley's-[^(L)]{\rm{\hat L}} Features. Bildverarbeitung für die Medizin 2011: 44-48 - [c25]Christian Loyek, Jan Kölling, Daniel Langenkämper
, Karsten Niehaus, Tim W. Nattkemper
:
A Web2.0 Strategy for the Collaborative Analysis of Complex Bioimages. IDA 2011: 258-269 - 2010
- [j19]Julia Herold, Luxian Zhou, Sylvie Abouna, Stella Pelengaris, David B. A. Epstein, Michael Khan
, Tim W. Nattkemper
:
Integrating semantic annotation and information visualization for the analysis of multichannel fluorescence micrographs from pancreatic tissue. Comput. Medical Imaging Graph. 34(6): 446-452 (2010)
2000 – 2009
- 2009
- [j18]Stefan P. Albaum, Heiko Neuweger, Benjamin Fränzel, Sita Lange, Dominik Mertens, Christian Trötschel
, Dirk Wolters, Jörn Kalinowski, Tim W. Nattkemper
, Alexander Goesmann
:
Qupe - a Rich Internet Application to take a step forward in the analysis of mass spectrometry-based quantitative proteomics experiments. Bioinform. 25(23): 3128-3134 (2009) - [j17]Naryttza N. Diaz, Lutz Krause
, Alexander Goesmann
, Karsten Niehaus, Tim W. Nattkemper
:
TACOA - Taxonomic classification of environmental genomic fragments using a kernelized nearest neighbor approach. BMC Bioinform. 10 (2009) - [j16]Axel Saalbach, Oliver Lange, Tim W. Nattkemper
, Anke Meyer-Baese
:
On the application of (topographic) independent and tree-dependent component analysis for the examination of DCE-MRI data. Biomed. Signal Process. Control. 4(3): 247-253 (2009) - [c24]Timm Schoening, Nils Ehnert, Jörg Ontrup, Tim W. Nattkemper
:
BIIGLE Tools - A Web 2.0 Approach for Visual Bioimage Database Mining. IV 2009: 51-56 - [c23]Julia Herold, Sylvie Abouna, Luxian Zhou, Stella Pelengaris, David B. A. Epstein, Michael Khan
, Tim W. Nattkemper
:
A way toward analyzing high-content bioimage data by means of semantic annotation and visual data mining. Medical Imaging: Image Processing 2009: 72591Q - 2008
- [j15]Christian Martin, Naryttza N. Diaz, Jörg Ontrup, Tim W. Nattkemper
:
Hyperbolic SOM-based clustering of DNA fragment features for taxonomic visualization and classification. Bioinform. 24(14): 1568-1574 (2008) - [j14]Wiebke Timm, Alexandra Scherbart, Sebastian Böcker
, Oliver Kohlbacher
, Tim W. Nattkemper
:
Peak intensity prediction in MALDI-TOF mass spectrometry: A machine learning study to support quantitative proteomics. BMC Bioinform. 9 (2008) - [j13]Ning Wei, Erwin Flaschel, Karl Friehs, Tim W. Nattkemper
:
A machine vision system for automated non-invasive assessment of cell viability via dark field microscopy, wavelet feature selection and classification. BMC Bioinform. 9 (2008) - [j12]Thorsten Twellmann, Anke Meyer-Bäse
, Oliver Lange, Simon Y. Foo, Tim W. Nattkemper
:
Model-free visualization of suspicious lesions in breast MRI based on supervised and unsupervised learning. Eng. Appl. Artif. Intell. 21(2): 129-140 (2008) - [c22]Julia Herold, Sylvie Abouna, Luxian Zhou, Stella Pelengaris, David B. A. Epstein, Michael Khan, Tim W. Nattkemper:
A machine learning based system for multichannel fluorescence analysis in pancreatic tissue bioimages. BIBE 2008: 1-6 - [c21]Christian Loyek, Friedrich G. Woermann, Tim W. Nattkemper
:
Detection of Focal Cortical Dysplasia Lesions in MRI Using Textural Features. Bildverarbeitung für die Medizin 2008: 432-436 - [c20]Christian Martin, Tim W. Nattkemper
:
A Tree Index to Support Clustering Based Exploratory Data Analysis. BIRD 2008: 1-15 - [c19]Alexandra Scherbart, Wiebke Timm, Sebastian Böcker
, Tim W. Nattkemper
:
Improved Mass Spectrometry Peak Intensity Prediction by Adaptive Feature Weighting. ICONIP (1) 2008: 513-520 - [c18]Alexandra Scherbart, Tim W. Nattkemper
:
The Diversity of Regression Ensembles Combining Bagging and Random Subspace Method. ICONIP (2) 2008: 911-918 - [c17]Julia Herold, Manuela Friedenberger, Marcus Bode, Nasir M. Rajpoot
, Walter Schubert
, Tim W. Nattkemper
:
Flexible synapse detection in fluorescence micrographs by modeling human expert grading. ISBI 2008: 1347-1350 - 2007
- [j11]Birgit Lessmann, Tim W. Nattkemper
, Volkmar H. Hans, Andreas Degenhard:
A method for linking computed image features to histological semantics in neuropathology. J. Biomed. Informatics 40(6): 631-641 (2007) - [c16]Alexandra Scherbart, Wiebke Timm, Sebastian Böcker, Tim W. Nattkemper
:
Neural Network Approach for Mass Spectrometry Prediction by Peptide Prototyping. ICANN (2) 2007: 90-99 - 2006
- [j10]Claudio Varini, Andreas Degenhard, Tim W. Nattkemper
:
Visual exploratory analysis of DCE-MRI data in breast cancer by dimensional data reduction: A comparative study. Biomed. Signal Process. Control. 1(1): 56-63 (2006) - [j9]Claudio Varini, Andreas Degenhard, Tim W. Nattkemper
:
ISOLLE: LLE with geodesic distance. Neurocomputing 69(13-15): 1768-1771 (2006) - [c15]Birgit Lessmann, Tim W. Nattkemper, Johannes Huth, Christian Loyek, Preminda Kessar, Michael Khazen, Linda Pointon, Martin O. Leach, Andreas Degenhard:
Content Based Image Retrieval for Dynamic Time Series Data. Bildverarbeitung für die Medizin 2006: 61-65 - [c14]Claudio Varini, Birgit Lessmann, Andreas Degenhard, Volkmar H. Hans, Tim W. Nattkemper:
Visual Exploration of Pathology Images by a Discrete Wavelet Transform Preprocessed Locally Linear Embedding. Bildverarbeitung für die Medizin 2006: 66-70 - [c13]Christian Martin, Harmen grosse Deters, Tim W. Nattkemper
:
Fusing Biomedical Multi-modal Data for Exploratory Data Analysis. ICANN (2) 2006: 798-807 - [c12]Birgit Lessmann, Volkmar H. Hans, Andreas Degenhard, Tim W. Nattkemper
:
Feature-space exploration of pathology images using content-based database visualization. Medical Imaging: Image Processing 2006: 61445Z - [c11]Claudio Varini, Andreas Degenhard, Tim W. Nattkemper
:
Histologic characterization of DCE-MRI breast tumors with dimensional data reduction. Medical Imaging: Image Processing 2006: 614462 - 2005
- [j8]Tim W. Nattkemper
, Bert Arnrich
, Oliver Lichte, Wiebke Timm, Andreas Degenhard, Linda Pointon, Carmel Hayes, Martin O. Leach
:
The UK MARIBS Breast Screening Study: Evaluation of radiological features for breast tumour classification in clinical screening with machine learning methods. Artif. Intell. Medicine 34(2): 129-139 (2005) - [j7]Axel Saalbach, Jörg Ontrup, Helge J. Ritter, Tim W. Nattkemper
:
Image fusion based on topographic mappings using the hyperbolic space. Inf. Vis. 4(3): 266-275 (2005) - [j6]Tim W. Nattkemper
, Axel Wismüller:
Tumor feature visualization with unsupervised learning. Medical Image Anal. 9(4): 344-351 (2005) - [j5]Thorsten Twellmann, Oliver Lichte, Tim W. Nattkemper
:
An adaptive tissue characterization network for model-free visualization of dynamic contrast-enhanced magnetic resonance image data. IEEE Trans. Medical Imaging 24(10): 1256-1266 (2005) - [c10]Axel Saalbach, Thorsten Twellmann, Tim W. Nattkemper, Axel Wismüller, Jörg Ontrup, Helge J. Ritter:
A Hyperbolic Topographic Mapping for Proximity Data. Artificial Intelligence and Applications 2005: 106-111 - [c9]Thorsten Twellmann, Oliver Lichte, Axel Saalbach, Axel Wismüller, Tim W. Nattkemper:
An Adaptive Extended Colour Scale for Comparison of Pseudo Colouring Techniques for DCE-MRI Data. Bildverarbeitung für die Medizin 2005: 312-316 - [c8]Birgit Lessmann, Andreas Degenhard, Preminda Kessar, Linda Pointon, Michael Khazen, Martin O. Leach
, Tim W. Nattkemper
:
SOM-Based Wavelet Filtering for the Exploration of Medical Images. ICANN (1) 2005: 671-676 - [c7]Claudio Varini, Andreas Degenhard, Tim W. Nattkemper
:
ISOLLE: Locally Linear Embedding with Geodesic Distance. PKDD 2005: 331-342 - 2004
- [j4]Tim W. Nattkemper
:
Multivariate image analysis in biomedicine. J. Biomed. Informatics 37(5): 380-391 (2004) - [c6]Tim W. Nattkemper:
Automatic segmentation of digital micrographs: A survey. MedInfo 2004: 847-851 - [c5]Axel Saalbach, Thorsten Twellmann, Tim W. Nattkemper
, Mark White, Michael Khazen, Martin O. Leach
:
Visualization of multivariate image data using image fusion and perceptually optimized color scales based on sRGB. Medical Imaging: Image-Guided Procedures 2004 - [c4]Andreas Degenhard, Marc Mutz, Tim W. Nattkemper, Axel Saalbach, Thorsten Twellmann, Mark J. White, Michael Khazen, Linda Pointon, Martin O. Leach
:
Multiscale entropy analysis in dynamic contrast-enhanced MRI. Medical Imaging: Image Processing 2004 - 2003
- [j3]Tim W. Nattkemper
, Thorsten Twellmann, Helge J. Ritter, Walter Schubert
:
Human vs. machine: evaluation of fluorescence micrographs. Comput. Biol. Medicine 33(1): 31-43 (2003) - 2002
- [j2]Tim W. Nattkemper
, Heiko Wersing, Walter Schubert
, Helge J. Ritter:
A neural network architecture for automatic segmentation of fluorescence micrographs. Neurocomputing 48(1-4): 357-367 (2002) - 2001
- [j1]Tim W. Nattkemper
, Helge J. Ritter, Walter Schubert
:
A neural classifier enabling high-throughput topological analysis of lymphocytes in tissue sections. IEEE Trans. Inf. Technol. Biomed. 5(2): 138-149 (2001) - [c3]Tanja Kämpfe, Tim W. Nattkemper, Helge J. Ritter:
Combining Independent Component Analysis and Self-Organizing Maps for Cell Image Classification. DAGM-Symposium 2001: 262-268 - 2000
- [c2]Tim W. Nattkemper, Heiko Wersing, Walter Schubert, Helge J. Ritter:
A neural network architecture for automatic segmentation of fluorescence micrographs. ESANN 2000: 177-182 - [c1]Tim W. Nattkemper, Heiko Wersing, Helge J. Ritter, Walter Schubert:
Fluorescence Micrograph Segmentation by Gestalt-Based Feature Binding. IJCNN (1) 2000: 348-353
Coauthor Index
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last updated on 2024-05-08 21:00 CEST by the dblp team
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