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TNN
2008
178views more  TNN 2008»
13 years 8 months ago
IMORL: Incremental Multiple-Object Recognition and Localization
This paper proposes an incremental multiple-object recognition and localization (IMORL) method. The objective of IMORL is to adaptively learn multiple interesting objects in an ima...
Haibo He, Sheng Chen
ECCV
2000
Springer
14 years 10 months ago
Learning Similarity for Texture Image Retrieval
A novel algorithm is proposed to learn pattern similarities for texture image retrieval. Similar patterns in di erent texture classes are grouped into a cluster in the feature spac...
Guodong Guo, Stan Z. Li, Kap Luk Chan
AIRS
2006
Springer
14 years 9 days ago
A Semantic Fusion Approach Between Medical Images and Reports Using UMLS
One of the main challenges in content-based image retrieval still remains to bridge the gap between low-level features and semantic information. In this paper, we present our first...
Daniel Racoceanu, Caroline Lacoste, Roxana Teodore...
KDD
2004
ACM
117views Data Mining» more  KDD 2004»
14 years 9 months ago
Regularized multi--task learning
Past empirical work has shown that learning multiple related tasks from data simultaneously can be advantageous in terms of predictive performance relative to learning these tasks...
Theodoros Evgeniou, Massimiliano Pontil
MM
2004
ACM
219views Multimedia» more  MM 2004»
14 years 2 months ago
Multi-level annotation of natural scenes using dominant image components and semantic concepts
Automatic image annotation is a promising solution to enable semantic image retrieval via keywords. In this paper, we propose a multi-level approach to annotate the semantics of n...
Jianping Fan, Yuli Gao, Hangzai Luo