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ISBI
2009
IEEE
14 years 2 months ago
Bridging the Semantic Gap Using Ranking Svm for Image Retrieval
One of the main challenges for Content-Based Image Retrieval (CBIR) is to achieve meaningful mappings between the high-level semantic concepts and the low-level visual features in...
Haiying Guan, Sameer Antani, L. Rodney Long, Georg...
MM
2010
ACM
192views Multimedia» more  MM 2010»
13 years 7 months ago
iLike: integrating visual and textual features for vertical search
Content-based image search on the Internet is a challenging problem, mostly due to the semantic gap between low-level visual features and high-level content, as well as the excess...
Yuxin Chen, Nenghai Yu, Bo Luo, Xue-wen Chen
ICMCS
2007
IEEE
131views Multimedia» more  ICMCS 2007»
14 years 1 months ago
Semantic Retrieval with Enhanced Matchmaking and Multi-Modality Ontology
This paper presents a method for automatically annotating and retrieving animal images. Our model is a multi-modality ontology extended from our previous works in the sense that b...
Huan Wang, Liang-Tien Chia, Song Liu
MM
2009
ACM
269views Multimedia» more  MM 2009»
14 years 1 months ago
Semi-supervised topic modeling for image annotation
We propose a novel technique for semi-supervised image annotation which introduces a harmonic regularizer based on the graph Laplacian of the data into the probabilistic semantic ...
Yuanlong Shao, Yuan Zhou, Xiaofei He, Deng Cai, Hu...
AVI
2008
13 years 9 months ago
Scenique: a multimodal image retrieval interface
Searching for images by using low-level visual features, such as color and texture, is known to be a powerful, yet imprecise, retrieval paradigm. The same is true if search relies...
Ilaria Bartolini, Paolo Ciaccia