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» Unsupervised Object Discovery: A Comparison
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AUSAI
2006
Springer
14 years 1 months ago
Clustering Similarity Comparison Using Density Profiles
The unsupervised nature of cluster analysis means that objects can be clustered in many different ways. This means that different clustering algorithms can lead to vastly different...
Eric Bae, James Bailey, Guozhu Dong
ICDM
2009
IEEE
109views Data Mining» more  ICDM 2009»
14 years 4 months ago
Knowledge Discovery from Citation Networks
—Knowledge discovery from scientific articles has received increasing attentions recently since huge repositories are made available by the development of the Internet and digit...
Zhen Guo, Zhongfei Zhang, Shenghuo Zhu, Yun Chi, Y...
ECCV
2006
Springer
14 years 11 months ago
Scene Classification Via pLSA
Given a set of images of scenes containing multiple object categories (e.g. grass, roads, buildings) our objective is to discover these objects in each image in an unsupervised man...
Anna Bosch, Andrew Zisserman, Xavier Muñoz
EACL
2006
ACL Anthology
13 years 11 months ago
The GOD model
GOD (General Ontology Discovery) is an unsupervised system to extract semantic relations among domain specific entities and concepts from texts. Operationally, it acts as a search...
Alfio Massimiliano Gliozzo
PAMI
2007
171views more  PAMI 2007»
13 years 9 months ago
Toward Objective Evaluation of Image Segmentation Algorithms
—Unsupervised image segmentation is an important component in many image understanding algorithms and practical vision systems. However, evaluation of segmentation algorithms thu...
Ranjith Unnikrishnan, Caroline Pantofaru, Martial ...