Erhardt Barth
Erhardt Barth
Professor of Computer Science, University of Lübeck
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Zitiert von
Zitiert von
Time‐of‐flight cameras in computer graphics
A Kolb, E Barth, R Koch, R Larsen
Computer Graphics Forum 29 (1), 141-159, 2010
Variability of eye movements when viewing dynamic natural scenes
M Dorr, T Martinetz, KR Gegenfurtner, E Barth
Journal of vision 10 (10), 28-28, 2010
Accurate eye centre localisation by means of gradients.
F Timm, E Barth
Visapp 11, 125-130, 2011
A multi-organ nucleus segmentation challenge
N Kumar, R Verma, D Anand, Y Zhou, OF Onder, E Tsougenis, H Chen, ...
IEEE transactions on medical imaging 39 (5), 1380-1391, 2019
A hybrid convolutional variational autoencoder for text generation
S Semeniuta, A Severyn, E Barth
arXiv preprint arXiv:1702.02390, 2017
How honeybees make grazing landings on flat surfaces
MV Srinivasan, SW Zhang, JS Chahl, E Barth, S Venkatesh
Biological cybernetics 83, 171-183, 2000
Recurrent dropout without memory loss
S Semeniuta, A Severyn, E Barth
arXiv preprint arXiv:1603.05118, 2016
Fundamental limits of linear filters in the visual processing of two-dimensional signals
C Zetzsche, E Barth
Vision research 30 (7), 1111-1117, 1990
Explainable COVID-19 detection using chest CT scans and deep learning
H Alshazly, C Linse, E Barth, T Martinetz
Sensors 21 (2), 455, 2021
Simple method for high-performance digit recognition based on sparse coding
K Labusch, E Barth, T Martinetz
IEEE Transactions on Neural Networks 19, 1985-1989, 2008
Deep convolutional neural networks as generic feature extractors
L Hertel, E Barth, T Käster, T Martinetz
2015 International Joint Conference on Neural Networks (IJCNN), 1-4, 2015
Low-level phenomenal vision despite unilateral destruction of primary visual cortex
P Stoerig, E Barth
Consciousness and cognition 10 (4), 574-587, 2001
The importance of intrinsically two-dimensional image features in biological vision and picture coding
C Zetzsche, E Barth, B Wegmann
Digital images and human vision, 109-138, 1993
Analysis of superimposed oriented patterns
T Aach, C Mota, I Stuke, M Muhlich, E Barth
IEEE Transactions on Image Processing 15 (12), 3690-3700, 2006
ToF-sensors: New dimensions for realism and interactivity
A Kolb, E Barth, R Koch
2008 IEEE Computer Society Conference on Computer Vision and Pattern …, 2008
Automated indirect immunofluorescence evaluation of antinuclear autoantibodies on HEp‐2 cells
J Voigt, C Krause, E Rohwäder, S Saschenbrecker, M Hahn, ...
Journal of Immunology Research 2012 (1), 651058, 2012
Image encoding, labeling, and reconstruction from differential geometry
E Barth, T Caelli, C Zetzsche
CVGIP: Graphical models and image processing 55 (6), 428-446, 1993
Ensembles of deep learning models and transfer learning for ear recognition
H Alshazly, C Linse, E Barth, T Martinetz
Sensors 19 (19), 4139, 2019
Non-parametric texture defect detection using Weibull features
F Timm, E Barth
Image Processing: Machine Vision Applications IV 7877, 150-161, 2011
Remote eye tracking: State of the art and directions for future development
M Bohme, A Meyer, T Martinetz, E Barth
Proc. of the 2006 Conference on Communication by Gaze Interaction (COGAIN …, 2006
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