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» Unsupervised discovery of repetitive objects
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ECCV
2008
Springer
13 years 9 months ago
Unsupervised Classification and Part Localization by Consistency Amplification
We present a novel method for unsupervised classification, including the discovery of a new category and precise object and part localization. Given a set of unlabelled images, som...
Leonid Karlinsky, Michael Dinerstein, Dan Levi, Sh...
MTA
2007
101views more  MTA 2007»
13 years 7 months ago
Finding maximum-length repeating patterns in music databases
Abstract This paper introduces the problem of discovering maximum-length repeating patterns in music objects. A novel algorithm is presented for the extraction of this kind of patt...
Ioannis Karydis, Alexandros Nanopoulos, Yannis Man...
CVPR
2011
IEEE
13 years 3 months ago
From Region Similarity to Category Discovery
The goal of object category discovery is to automatically identify groups of image regions which belong to some new, previously unseen category. This task is typically performed i...
Carolina Galleguillos, Brian McFee, Serge Belongie...
WWW
2008
ACM
14 years 8 months ago
Unsupervised query segmentation using generative language models and wikipedia
In this paper, we propose a novel unsupervised approach to query segmentation, an important task in Web search. We use a generative query model to recover a query's underlyin...
Bin Tan, Fuchun Peng
ICPR
2006
IEEE
14 years 8 months ago
Latent Layout Analysis for Discovering Objects in Images
Latent Layout Analysis (LLA) is a novel unsupervised learning technique to discover objects in unseen images using a set of un-annotated training images. LLA defines a generative ...
David Liu, Datong Chen, Tsuhan Chen