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» Using Maximum Entropy for Automatic Image Annotation
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MM
2006
ACM
190views Multimedia» more  MM 2006»
14 years 1 months ago
Image annotation refinement using random walk with restarts
Image annotation plays an important role in image retrieval and management. However, the results of the state-of-the-art image annotation methods are often unsatisfactory. Therefo...
Changhu Wang, Feng Jing, Lei Zhang, HongJiang Zhan...
MIR
2006
ACM
200views Multimedia» more  MIR 2006»
14 years 1 months ago
An adaptive graph model for automatic image annotation
Automatic keyword annotation is a promising solution to enable more effective image search by using keywords. In this paper, we propose a novel automatic image annotation method b...
Jing Liu, Mingjing Li, Wei-Ying Ma, Qingshan Liu, ...
ACL
2008
13 years 9 months ago
Word Clustering and Word Selection Based Feature Reduction for MaxEnt Based Hindi NER
Statistical machine learning methods are employed to train a Named Entity Recognizer from annotated data. Methods like Maximum Entropy and Conditional Random Fields make use of fe...
Sujan Kumar Saha, Pabitra Mitra, Sudeshna Sarkar
LREC
2008
131views Education» more  LREC 2008»
13 years 9 months ago
Learning Morphology with Morfette
Morfette is a modular, data-driven, probabilistic system which learns to perform joint morphological tagging and lemmatization from morphologically annotated corpora. The system i...
Grzegorz Chrupala, Georgiana Dinu, Josef van Genab...
ICMCS
2006
IEEE
124views Multimedia» more  ICMCS 2006»
14 years 1 months ago
Content-Free Image Retrieval using Bayesian Product Rule
Content-free image retrieval uses accumulated user feedback records to retrieve images without analyzing image pixels. We present a Bayesian-based algorithm to analyze user feedba...
David Liu, Tsuhan Chen