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Beschreibung
This book constitutes the refereed post-proceedings of the First PASCAL Machine Learning Challenges Workshop, MLCW 2005. 25 papers address three challenges: finding an assessment base on the uncertainty of predictions using classical statistics, Bayesian inference, and statistical learning theory; second, recognizing objects from a number of visual object classes in realistic scenes; third, recognizing textual entailment addresses semantic analysis of language to form a generic framework for applied semantic inference in text understanding.
Evaluating Predictive Uncertainty, Visual Object Classification, and Recognizing Textual Entailment, First Pascal Machine Learning Challenges Workshop, MLCW 2005, Southampton, UK, April 11-13, 2005, Revised Selected Papers
Details
| Verlag | Springer Berlin |
| Ersterscheinung | 11. Mai 2006 |
| Maße | 23.5 cm x 15.5 cm |
| Gewicht | 815 Gramm |
| Format | Softcover |
| ISBN-13 | 9783540334279 |
| Seiten | 462 |
Schlagwörter
Algorithmen und Datenstrukturen, Algorithms, Artificial Intelligence, Automated Pattern Recognition, Computer Vision, Formal Languages and Automata Theory, Künstliche Intelligenz, Maschinelles Sehen - Bildverstehen, Mustererkennung, Natural Language Processing (NLP), Natürliche Sprachen und maschinelle Übersetzung, Theoretische Informatik
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