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Endoscope Distortion Correction Does Not (Easily) Improve Mucosa-Based Classification of Celiac Disease.

J. Hämmerle-Uhl, Y. Höller, A. Uhl, and A. Vécsei. MICCAI (3), volume 7512 of Lecture Notes in Computer Science, page 574-581. Springer, (2012)

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Prof. Dr. Andreas Hotho

Ontology-based Text Document Clustering.A. Hotho, A. Maedche, and S. Staab. KI, 16 (4): 48-54 (2002)

Ontology-based Text Document Clustering.A. Hotho, A. Maedche, and S. Staab. KI, 16 (4): 48-54 (2002)Clustern mit Hintergrundwissen.A. Hotho. Karlsruhe Institute of Technology, (2004)

Junior-Prof. Dr.-Ing. Andreas Pott

Andreas Kaufmann

Andreas Pahler University of Stuttgart

Hon. -Prof. Dr. -Ing. Andreas Pott University of Stuttgart

Other publications of authors with the same name

Feature extraction from multi-directional multi-resolution image transformations for the classification of zoom-endoscopy images.M. Häfner, R. Kwitt, A. Uhl, A. Gangl, F. Wrba, and A. Vécsei. Pattern Anal. Appl., 12 (4): 407-413 (2009)Complex Wavelet Transform Variants in a Scale Invariant Classification of Celiac Disease.A. Uhl, A. Vécsei, and G. Wimmer. IbPRIA, volume 6669 of Lecture Notes in Computer Science, page 742-749. Springer, (2011)Endoscope Distortion Correction Does Not (Easily) Improve Mucosa-Based Classification of Celiac Disease.J. Hämmerle-Uhl, Y. Höller, A. Uhl, and A. Vécsei. MICCAI (3), volume 7512 of Lecture Notes in Computer Science, page 574-581. Springer, (2012)Improved endoscope distortion correction does not necessarily enhance mucosa-classification based medical decision support systems.M. Gschwandtner, J. Hämmerle-Uhl, Y. Höller, M. Liedlgruber, A. Uhl, and A. Vécsei. MMSP, page 158-163. IEEE, (2012)Incorporating human knowledge in automated celiac disease diagnosis.M. Gadermayr, H. Kogler, M. Karla, A. Vécsei, A. Uhl, and D. Merhof. IPTA, page 1-6. IEEE, (2016)Narrow band imaging versus white-light: What is best for computer-assisted diagnosis of celiac disease?M. Gadermayr, S. Hegenbart, R. Kwitt, A. Uhl, and A. Vécsei. ISBI, page 355-359. IEEE, (2016)Automated Marsh-like classification of celiac disease in children using local texture operators.A. Vécsei, G. Amann, S. Hegenbart, M. Liedlgruber, and A. Uhl. Comp. in Bio. and Med., 41 (6): 313-325 (2011)Convolutional Neural Network Architectures for the Automated Diagnosis of Celiac Disease.G. Wimmer, S. Hegenbart, A. Vécsei, and A. Uhl. CARE@MICCAI, volume 10170 of Lecture Notes in Computer Science, page 104-113. Springer, (2016)Do We Need Annotation Experts? A Case Study in Celiac Disease Classification.R. Kwitt, S. Hegenbart, N. Rasiwasia, A. Vécsei, and A. Uhl. MICCAI (2), volume 8674 of Lecture Notes in Computer Science, page 454-461. Springer, (2014)Feature Extraction with Intrinsic Distortion Correction in Celiac Disease Imagery: No Need for Rasterization.M. Gadermayr, A. Uhl, and A. Vécsei. MCV, volume 8331 of Lecture Notes in Computer Science, page 196-204. Springer, (2013)