- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- ISBN
-
9783933218315
- Dimensions
-
21 cm
- Extent
-
XX, 208 S.
- Language
-
Englisch
- Notes
-
graph. Darst.
Zugl.: Saarbrücken, Univ., Diss., 2011
- Bibliographic citation
-
Saarbrücken dissertations in computational linguistics and language technology ; Vol. 32
- Event
-
Veröffentlichung
- (where)
-
Saarbrücken
- (who)
-
German Research Center for Artificial Intelligence
- (when)
-
2011
- Event
-
Veröffentlichung
- (where)
-
Saarbrücken
- (who)
-
Saarland Univ., Dep. of Computational Linguistics and Phonetics
- (when)
-
2011
- Creator
- Table of contents
- Rights
-
Bei diesem Objekt liegt nur das Inhaltsverzeichnis digital vor. Der Zugriff darauf ist unbeschränkt möglich.
- Last update
-
11.06.2025, 1:43 PM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Object type
- Hochschulschrift
Associated
- Fürstenau, Hagen
- German Research Center for Artificial Intelligence
- Saarland Univ., Dep. of Computational Linguistics and Phonetics
Time of origin
- 2011
Other Objects (12)
Exploring semi-supervised methods for labeling support in multimodal datasets
Semantic-Fusion Gans for Semi-Supervised Satellite Image Classification
Semantic-Fusion Gans for Semi-Supervised Satellite Image Classification
Improving Semi-Supervised and Domain-Adaptive Semantic Segmentation with Self-Supervised Depth Estimation
Pseudo-label noise suppression techniques for semi-supervised semantic segmentation
Semi-supervised data cleaning
Evaluation of semi-supervised learning using sparse labeling to segment cell nuclei
Efficient and accurate semi-supervised semantic segmentation for industrial surface defects
Semi-supervised structured prediction models
Semi-supervised protein subcellular localization
Semi-supervised learning for image classification
A survey on semi-supervised learning
Exploring semi-supervised methods for labeling support in multimodal datasets
Semantic-Fusion Gans for Semi-Supervised Satellite Image Classification
Semantic-Fusion Gans for Semi-Supervised Satellite Image Classification
Improving Semi-Supervised and Domain-Adaptive Semantic Segmentation with Self-Supervised Depth Estimation
Pseudo-label noise suppression techniques for semi-supervised semantic segmentation
Semi-supervised data cleaning
Evaluation of semi-supervised learning using sparse labeling to segment cell nuclei
Efficient and accurate semi-supervised semantic segmentation for industrial surface defects
Semi-supervised structured prediction models
Semi-supervised protein subcellular localization
Semi-supervised learning for image classification
A survey on semi-supervised learning
Exploring semi-supervised methods for labeling support in multimodal datasets
Semantic-Fusion Gans for Semi-Supervised Satellite Image Classification
Semantic-Fusion Gans for Semi-Supervised Satellite Image Classification
Improving Semi-Supervised and Domain-Adaptive Semantic Segmentation with Self-Supervised Depth Estimation
Pseudo-label noise suppression techniques for semi-supervised semantic segmentation
Semi-supervised data cleaning
Evaluation of semi-supervised learning using sparse labeling to segment cell nuclei
Efficient and accurate semi-supervised semantic segmentation for industrial surface defects
Semi-supervised structured prediction models
Semi-supervised protein subcellular localization
Semi-supervised learning for image classification