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» An objective evaluation criterion for clustering
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SDM
2008
SIAM
139views Data Mining» more  SDM 2008»
13 years 10 months ago
Simultaneous Unsupervised Learning of Disparate Clusterings
Most clustering algorithms produce a single clustering for a given data set even when the data can be clustered naturally in multiple ways. In this paper, we address the difficult...
Prateek Jain, Raghu Meka, Inderjit S. Dhillon
CVPR
2007
IEEE
14 years 11 months ago
Learning Visual Similarity Measures for Comparing Never Seen Objects
In this paper we propose and evaluate an algorithm that learns a similarity measure for comparing never seen objects. The measure is learned from pairs of training images labeled ...
Eric Nowak, Frédéric Jurie
ICDAR
2011
IEEE
12 years 8 months ago
A New Fourier-Moments Based Video Word and Character Extraction Method for Recognition
— This paper presents a new method based on Fourier and moments features to extract words and characters from a video text line in any direction for recognition. Unlike existing ...
Deepak Rajendran, Palaiahnakote Shivakumara, Bolan...
ICRA
1998
IEEE
91views Robotics» more  ICRA 1998»
14 years 1 months ago
Selecting Targets for Local Reference Frames
This paper addresses the problem of seeking out parts of the environment that provide adequate features in order to perform robot localization. The objective is to choose good regi...
Saul Simhon, Gregory Dudek
TIP
2008
85views more  TIP 2008»
13 years 9 months ago
A Scale-Based Connected Coherence Tree Algorithm for Image Segmentation
This paper presents a connected coherence tree algorithm (CCTA) for image segmentation with no prior knowledge. It aims to find regions of semantic coherence based on the proposed ...
Jundi Ding, RuNing Ma, Songcan Chen