Zobrazeno 1 - 10
of 80
pro vyhledávání: '"Rolf P Würtz"'
Publikováno v:
PLoS ONE, Vol 9, Iss 11, p e109033 (2014)
Data transformations prior to analysis may be beneficial in classification tasks. In this article we investigate a set of such transformations on 2D graph-data derived from facial images and their effect on classification accuracy in a high-dimension
Externí odkaz:
https://doaj.org/article/e8747c139c4b4ab688d7d5f6e44ae152
Autor:
Rolf P. Würtz
Publikováno v:
INTELLIGENT BIOMETRIC TECHNIQUES in FINGERPRINT and FACE RECOGNITION ISBN: 9780203750520
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0f25b76480fcb2134ade49679fcd3f58
https://doi.org/10.1201/9780203750520-10
https://doi.org/10.1201/9780203750520-10
Autor:
Robert P Kosilek, Richard Frohner, Harald Jörn Schneider, G. K. Stalla, M. Witt, Stephanie Zopp, ChristinaM. Berr, AnastasiaP. Athanasoulia-Kaspar, Rolf P. Würtz, Martin Reincke, Kathrin H. Popp, Timo Deutschbein, Marcus Quinkler
Publikováno v:
Experimental and Clinical Endocrinology & Diabetes. 127:685-690
Objective Cushing’s syndrome is a rare disease characterized by clinical features that show morphological similarity with the metabolic syndrome. Distinguishing these diseases in clinical practice is challenging. We have previously shown that compu
Autor:
Rolf P. Würtz, Thomas Walther
Publikováno v:
Cognitive Systems Research. 47:68-84
Unsupervised learning of a generalizable model of the visual appearance of humans from video data is of major importance for computing systems interacting naturally with their users and others. We propose a step towards automatic behavior understandi
Autor:
Bernhard Sick, Martin Hoffmann, Arno Wacker, Wolfgang Reif, Gero Mühl, Gregor Schiele, Wolfgang Karl, Jean Botev, Chris Landauer, Kirstie L. Bellman, Ada Diaconescu, Claudio J. Tessone, Hella Ponsar, Lukas Esterle, Erik Maehle, Kurt Geihs, Anthony Stein, Uwe Brinkschulte, Stefan Rudolph, Christopher Stewart, Peter R. Lewis, Rolf P. Würtz, Sven Tomforde, Christian Müller-Schloer
Publikováno v:
2018 IEEE 3rd International Workshops on Foundations and Applications of Self* Systems (FAS*W).
Autor:
Rolf P. Würtz, Sven Tomforde, Ada Diaconescu, Christian Gruhl, Jean Botev, Peter R. Lewis, Kirstie L. Bellman, Chris Landauer, Anthony Stein, Lukas Esterle
Publikováno v:
FAS*W@SASO/ICAC
The self-improving system integration (SISSY) initiative has emerged in recent years in response to a systems engineering trend towards the organisation of open, interconnected systems integrating a large set of heterogeneous and autonomous subsystem
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::22425f6efc116ce2ba58b3936409d10f
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/73127
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/73127
Autor:
Richard Frohner, Harald Jörn Schneider, Jochen Schopohl, Martin Reincke, Christina M. Berr, Robert P Kosilek, Rolf P. Würtz
Publikováno v:
European Journal of Endocrinology. 173:M39-M44
Cushing's syndrome (CS) and acromegaly are endocrine diseases that are currently diagnosed with a delay of several years from disease onset. Novel diagnostic approaches and increased awareness among physicians are needed. Face classification technolo
Autor:
Raul Grieben, Rolf P. Würtz
Publikováno v:
FAS*W@SASO/ICCAC
Similarity rank lists provide a method for learning generalization of classifiers from examples. Here, we apply it to invariant object recognition and demonstrate that it performs better than other approaches on view and illumination invariant recogn
Autor:
Markus Lessmann, Rolf P. Würtz
Publikováno v:
Neural Networks. 54:70-84
Invariant object recognition, which means the recognition of object categories independent of conditions like viewing angle, scale and illumination, is a task of great interest that humans can fulfill much better than artificial systems. During the l
Autor:
Gamal Fahmy, Rolf P. Würtz
Publikováno v:
ISSPIT
Many recent techniques in forgery detection tried to counter noise dithering, which is well adopted in removing footprints of JPEG editing in any image tampering (anti forensics) process. In this paper we present a novel idea of detecting this noise