Andreas K. Maier
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Позовавания
Позовавания
Година
Robust vessel segmentation in fundus images
A Budai, R Bock, A Maier, J Hornegger, G Michelson
International journal of biomedical imaging 2013, 2013
2822013
A gentle introduction to deep learning in medical image processing
A Maier, C Syben, T Lasser, C Riess
Zeitschrift für Medizinische Physik 29 (2), 86-101, 2019
2062019
PEAKS–A system for the automatic evaluation of voice and speech disorders
A Maier, T Haderlein, U Eysholdt, F Rosanowski, A Batliner, M Schuster, ...
Speech Communication 51 (5), 425-437, 2009
1922009
Towards more reality in the recognition of emotional speech
B Schuller, D Seppi, A Batliner, A Maier, S Steidl
2007 IEEE international conference on acoustics, speech and signal …, 2007
1622007
Multi-scale deep reinforcement learning for real-time 3D-landmark detection in CT scans
FC Ghesu, B Georgescu, Y Zheng, S Grbic, A Maier, J Hornegger, ...
IEEE transactions on pattern analysis and machine intelligence 41 (1), 176-189, 2017
1452017
CONRAD—A software framework for cone‐beam imaging in radiology
A Maier, HG Hofmann, M Berger, P Fischer, C Schwemmer, H Wu, ...
Medical physics 40 (11), 111914, 2013
1442013
Age and gender recognition for telephone applications based on gmm supervectors and support vector machines
T Bocklet, A Maier, JG Bauer, F Burkhardt, E Noth
2008 IEEE International Conference on Acoustics, Speech and Signal …, 2008
1422008
Evaluation of speech intelligibility for children with cleft lip and palate by means of automatic speech recognition
M Schuster, A Maier, T Haderlein, E Nkenke, U Wohlleben, F Rosanowski, ...
International Journal of Pediatric Otorhinolaryngology 70 (10), 1741-1747, 2006
1292006
Robust non-rigid registration through agent-based action learning
J Krebs, T Mansi, H Delingette, L Zhang, FC Ghesu, S Miao, AK Maier, ...
International Conference on Medical Image Computing and Computer-Assisted …, 2017
1272017
Automatic classification of cancerous tissue in laserendomicroscopy images of the oral cavity using deep learning
M Aubreville, C Knipfer, N Oetter, C Jaremenko, E Rodner, J Denzler, ...
Scientific reports 7 (1), 1-10, 2017
1152017
Deep learning computed tomography: Learning projection-domain weights from image domain in limited angle problems
T Würfl, M Hoffmann, V Christlein, K Breininger, Y Huang, M Unberath, ...
IEEE transactions on medical imaging 37 (6), 1454-1463, 2018
1132018
Deep learning computed tomography
T Würfl, FC Ghesu, V Christlein, A Maier
International conference on medical image computing and computer-assisted …, 2016
1082016
Learning to recognize abnormalities in chest x-rays with location-aware dense networks
S Guendel, S Grbic, B Georgescu, S Liu, A Maier, D Comaniciu
Iberoamerican Congress on Pattern Recognition, 757-765, 2018
1022018
Automatic classification of defective photovoltaic module cells in electroluminescence images
S Deitsch, V Christlein, S Berger, C Buerhop-Lutz, A Maier, F Gallwitz, ...
Solar Energy 185, 455-468, 2019
982019
Toward quantitative optical coherence tomography angiography: visualizing blood flow speeds in ocular pathology using variable interscan time analysis
SB Ploner, EM Moult, WJ Choi, NK Waheed, BK Lee, EA Novais, ED Cole, ...
Retina 36, S118-S126, 2016
802016
Writer identification using GMM supervectors and exemplar-SVMs
V Christlein, D Bernecker, F Hönig, A Maier, E Angelopoulou
Pattern Recognition 63, 258-267, 2017
762017
Robust multiframe super-resolution employing iteratively re-weighted minimization
T Köhler, X Huang, F Schebesch, A Aichert, A Maier, J Hornegger
IEEE Transactions on Computational Imaging 2 (1), 42-58, 2016
722016
Adversarial and perceptual refinement for compressed sensing MRI reconstruction
M Seitzer, G Yang, J Schlemper, O Oktay, T Würfl, V Christlein, T Wong, ...
International conference on medical image computing and computer-assisted …, 2018
712018
Learning with known operators reduces maximum error bounds
AK Maier, C Syben, B Stimpel, T Würfl, M Hoffmann, F Schebesch, W Fu, ...
Nature machine intelligence 1 (8), 373-380, 2019
702019
Deep Learning for Magnetic Resonance Fingerprinting: A New Approach for Predicting Quantitative Parameter Values from Time Series.
E Hoppe, G Körzdörfer, T Würfl, J Wetzl, F Lugauer, J Pfeuffer, AK Maier
GMDS 243, 202-206, 2017
702017
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Статии 1–20