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» What are the high-level concepts with small semantic gaps
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TKDE
2008
195views more  TKDE 2008»
13 years 5 months ago
Learning a Maximum Margin Subspace for Image Retrieval
One of the fundamental problems in Content-Based Image Retrieval (CBIR) has been the gap between low-level visual features and high-level semantic concepts. To narrow down this gap...
Xiaofei He, Deng Cai, Jiawei Han
ESWA
2007
136views more  ESWA 2007»
13 years 6 months ago
Semantic-based facial expression recognition using analytical hierarchy process
In this paper we present an automatic facial expression recognition system that utilizes a semantic-based learning algorithm using the analytical hierarchy process (AHP). Although...
Shyi-Chyi Cheng, Ming-Yao Chen, Hong-Yi Chang, Tzu...
GI
1997
Springer
13 years 10 months ago
Functional Object-Oriented Programming with Object-Gofer
Object-Gofer is a small, practical extension of the functional programming language Gofer incorporating the following ideas from the object-oriented community: objects and toplevel...
Wolfram Schulte, Klaus Achatz
MIR
2004
ACM
171views Multimedia» more  MIR 2004»
13 years 11 months ago
Mean version space: a new active learning method for content-based image retrieval
In content-based image retrieval, relevance feedback has been introduced to narrow the gap between low-level image feature and high-level semantic concept. Furthermore, to speed u...
Jingrui He, Hanghang Tong, Mingjing Li, HongJiang ...
ICASSP
2007
IEEE
14 years 10 days ago
Integrating Relevance Feedback in Boosting for Content-Based Image Retrieval
Many content-based image retrieval applications suffer from small sample set and high dimensionality problems. Relevance feedback is often used to alleviate those problems. In thi...
Jie Yu, Yijuan Lu, Yuning Xu, Nicu Sebe, Qi Tian