Fred A. Hamprecht
Fred A. Hamprecht
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TitelZitiert vonJahr
Development and assessment of new exchange-correlation functionals
FA Hamprecht, AJ Cohen, DJ Tozer, NC Handy
The Journal of chemical physics 109 (15), 6264-6271, 1998
Ilastik: Interactive learning and segmentation toolkit
C Sommer, C Straehle, U Koethe, FA Hamprecht
2011 IEEE international symposium on biomedical imaging: From nano to macro …, 2011
A comparative study of modern inference techniques for discrete energy minimization problems
J Kappes, B Andres, F Hamprecht, C Schnorr, S Nowozin, D Batra, S Kim, ...
Proceedings of the IEEE conference on computer vision and pattern …, 2013
A comparison of random forest and its Gini importance with standard chemometric methods for the feature selection and classification of spectral data
BH Menze, BM Kelm, R Masuch, U Himmelreich, P Bachert, W Petrich, ...
BMC bioinformatics 10 (1), 213, 2009
Three-dimensional quantitative similarity− activity relationships (3D QSiAR) from SEAL similarity matrices
H Kubinyi, FA Hamprecht, T Mietzner
Journal of medicinal chemistry 41 (14), 2553-2564, 1998
Visualizing a homogeneous blend in bulk heterojunction polymer solar cells by analytical electron microscopy
M Pfannmöller, H Flugge, G Benner, I Wacker, C Sommer, ...
Nano letters 11 (8), 3099-3107, 2011
On oblique random forests
BH Menze, BM Kelm, DN Splitthoff, U Koethe, FA Hamprecht
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2011
Robust prediction of the MASCOT score for an improved quality assessment in mass spectrometric proteomics
T Koenig, BH Menze, M Kirchner, F Monigatti, KC Parker, T Patterson, ...
Journal of proteome research 7 (9), 3708-3717, 2008
Automated detection and segmentation of synaptic contacts in nearly isotropic serial electron microscopy images
A Kreshuk, CN Straehle, C Sommer, U Koethe, M Cantoni, G Knott, ...
PloS one 6 (10), e24899, 2011
Learning to count with regression forest and structured labels
L Fiaschi, U Köthe, R Nair, FA Hamprecht
Proceedings of the 21st International Conference on Pattern Recognition …, 2012
Segmentation of SBFSEM volume data of neural tissue by hierarchical classification
B Andres, U Köthe, M Helmstaedter, W Denk, FA Hamprecht
Joint Pattern Recognition Symposium, 142-152, 2008
Theoretical and experimental error analysis of continuous-wave time-of-flight range cameras
M Frank, M Plaue, H Rapp, U Köthe, B Jähne, FA Hamprecht
Optical Engineering 48 (1), 013602, 2009
Multi-modal brain tumor segmentation using deep convolutional neural networks
G Urban, M Bendszus, F Hamprecht, J Kleesiek
MICCAI BraTS (Brain Tumor Segmentation) Challenge. Proceedings, winning …, 2014
Concise representation of mass spectrometry images by probabilistic latent semantic analysis
M Hanselmann, M Kirchner, BY Renard, ER Amstalden, K Glunde, ...
Analytical chemistry 80 (24), 9649-9658, 2008
An objective comparison of cell-tracking algorithms
V Ulman, M Maška, KEG Magnusson, O Ronneberger, C Haubold, ...
Nature methods 14 (12), 1141, 2017
NITPICK: peak identification for mass spectrometry data
BY Renard, M Kirchner, H Steen, JAJ Steen, FA Hamprecht
BMC bioinformatics 9 (1), 355, 2008
Different phosphorylation states of the anaphase promoting complex in response to antimitotic drugs: a quantitative proteomic analysis
JAJ Steen, H Steen, A Georgi, K Parker, M Springer, M Kirchner, ...
Proceedings of the National Academy of Sciences 105 (16), 6069-6074, 2008
Globally optimal closed-surface segmentation for connectomics
B Andres, T Kroeger, KL Briggman, W Denk, N Korogod, G Knott, ...
European Conference on Computer Vision, 778-791, 2012
Probabilistic image segmentation with closedness constraints
B Andres, JH Kappes, T Beier, U Köthe, FA Hamprecht
2011 International Conference on Computer Vision, 2611-2618, 2011
When less can yield more–computational preprocessing of MS/MS spectra for peptide identification
BY Renard, M Kirchner, F Monigatti, AR Ivanov, J Rappsilber, D Winter, ...
Proteomics 9 (21), 4978-4984, 2009
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