Zobrazeno 1 - 10
of 36
pro vyhledávání: '"Reinhard Kneser"'
Publikováno v:
INTERSPEECH
The goal of this paper is to simulate the benefits of jointly applying active learning (AL) and semi-supervised training (SST) in a new speech recognition application. Our data selection approach relies on confidence filtering, and its impact on both
Autor:
H. Bartosik, Dieter Geller, W. Höllerbauer, Reinhold Haeb-Umbach, Bach-Hiep Tran, Hermann Dr Ney, Ute Essen, Xavier L. Aubert, Christian Dugast, H.-G. Meier, Martin Oerder, Reinhard Kneser, Volker Steinbiss
Publikováno v:
Speech Communication. 17:19-38
This paper gives an overview of the Philips research system for phoneme-based, large-vocabulary, continuousspeech recognition. The system has been successfully applied to various tasks in the German and (American) English languages, ranging from smal
Autor:
Ute Essen, Bach Hiep Tran, Hermann Ney, Reinhard Kneser, Stefan Besling, Hans Günter Meier, Martin Oerder, Dieter Geller, Xavier L. Aubert, Christian Dugast, Volker Steinbiss, Reinhold Haeb-Umbach
Publikováno v:
Philips Journal of Research. 49:317-352
This paper gives an overview of the Philips Research system for continuous-speech recognition. The recognition architecture is based on an integrated statistical approach. The system has been successfully applied to various tasks in American English
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence. 17:1202-1212
We apply the leaving-one-out concept to the estimation of 'small' probabilities, i.e., the case where the number of training samples is much smaller than the number of possible classes. After deriving the Turing-Good formula in this framework, we int
Publikováno v:
Computer Speech & Language. 8:1-38
In this paper, we study the problem of stochastic language modelling from the viewpoint of introducing suitable structures into the conditional probability distributions. The task of these distributions is to predict the probability of a new word by
Autor:
Axel, Saalbach, Irina, Wächter-Stehle, Reinhard, Kneser, Sabine, Mollus, Jochen, Peters, Jürgen, Weese
Publikováno v:
Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. 14(Pt 3)
With automated image analysis tools entering rapidly the clinical practice, the demands regarding reliability, accuracy, and speed are strongly increasing. Systematic testing approaches to determine optimal parameter settings and to select algorithm
Autor:
Jochen Peters, Axel Saalbach, Irina Wächter-Stehle, Jürgen Weese, Reinhard Kneser, Sabine Mollus
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783642236259
MICCAI (3)
MICCAI (3)
With automated image analysis tools entering rapidly the clinical practice, the demands regarding reliability, accuracy, and speed are strongly increasing. Systematic testing approaches to determine optimal parameter settings and to select algorithm
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d73c62d6991aba2f2568df7bca61947a
https://doi.org/10.1007/978-3-642-23626-6_57
https://doi.org/10.1007/978-3-642-23626-6_57
Autor:
Stewart Young, Lyubomir Georgiev Zagorchev, Carsten Meyer, Thomas Stehle, Juergen Weese, Reinhard Kneser
Publikováno v:
Multimodal Brain Image Analysis ISBN: 9783642244452
MBIA
MBIA
Traumatic brain injury (TBI) is often associated with life long neurobehavioral effects in survivors. Imaging has historically supported the detection and acute management of life-threatening complications. However, in order to predict these long ter
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b541a07a7349386a816a6340f4908295
https://doi.org/10.1007/978-3-642-24446-9_15
https://doi.org/10.1007/978-3-642-24446-9_15
Autor:
Cristian Lorenz, Jürgen Weese, Hans Barschdorf, Helko Lehmann, Raghed Hanna, Frank Weber, Irina Wächter, Olaf Dössel, Carsten Meyer, Reinhard Kneser, Jochen Peters, Olivier Ecabert
Publikováno v:
Statistical Atlases and Computational Models of the Heart ISBN: 9783642158346
STACOM/CESC
STACOM/CESC
A framework for the automatic extraction and generation of patient-specific organ models from different image modalities is presented. These models can be used to extract and represent diagnostic information about the heart and its function. Furtherm
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9894152c20e67c790a52ec9cf60fb194
https://doi.org/10.1007/978-3-642-15835-3_3
https://doi.org/10.1007/978-3-642-15835-3_3
Autor:
Jochen Peters, I. Wächter, Reinhard Kneser, Mani Vembar, Jonathan Lessick, Olivier Ecabert, Jürgen Weese
Publikováno v:
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2010 ISBN: 9783642157042
MICCAI (1)
MICCAI (1)
In recent years, the fully automatic segmentation of the whole heart from three-dimensional (3D) CT or MR images has become feasible with mean surface accuracies in the order of 1mm. The assessment of local myocardial motion and wall thickness for di
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::618824e51c65e85aa5e372fd89659b13
https://doi.org/10.1007/978-3-642-15705-9_49
https://doi.org/10.1007/978-3-642-15705-9_49