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» Learning Distance Functions for Image Retrieval
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ICML
2004
IEEE
14 years 8 months ago
Boosting margin based distance functions for clustering
The performance of graph based clustering methods critically depends on the quality of the distance function, used to compute similarities between pairs of neighboring nodes. In t...
Tomer Hertz, Aharon Bar-Hillel, Daphna Weinshall
ICMCS
2005
IEEE
184views Multimedia» more  ICMCS 2005»
14 years 1 months ago
Fuzzy relevance feedback in content-based image retrieval systems using radial basis function network
This paper presents a new framework called fuzzy relevance feedback in interactive content-based image retrieval (CBIR) systems based on soft-decision. An efficient learning appro...
Kim-Hui Yap, Kui Wu
CVPR
2010
IEEE
14 years 3 months ago
SPEC Hashing: Similarity Preserving algorithm for Entropy-based Coding
Searching approximate nearest neighbors in large scale high dimensional data set has been a challenging problem. This paper presents a novel and fast algorithm for learning binary...
Ruei-Sung Lin, David Ross, Jay Yagnik
CVPR
2008
IEEE
14 years 9 months ago
Coherent image annotation by learning semantic distance
Conventional approaches to automatic image annotation usually suffer from two problems: (1) They cannot guarantee a good semantic coherence of the annotated words for each image, ...
Tao Mei, Yong Wang, Xian-Sheng Hua, Shaogang Gong,...
NPL
2006
172views more  NPL 2006»
13 years 7 months ago
Adapting RBF Neural Networks to Multi-Instance Learning
In multi-instance learning, the training examples are bags composed of instances without labels, and the task is to predict the labels of unseen bags through analyzing the training...
Min-Ling Zhang, Zhi-Hua Zhou