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» On Feature Selection through Clustering
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SMI
2010
IEEE
188views Image Analysis» more  SMI 2010»
13 years 6 months ago
Sharp Feature Detection in Point Clouds
—This paper presents a new technique for detecting sharp features on point-sampled geometry. Sharp features of different nature and possessing angles varying from obtuse to acute...
Christopher Weber, Stefanie Hahmann, Hans Hagen
ICDAR
2003
IEEE
14 years 1 months ago
Features for Word Spotting in Historical Manuscripts
For the transition from traditional to digital libraries, the large number of handwritten manuscripts that exist pose a great challenge. Easy access to such collections requires a...
Toni M. Rath, R. Manmatha
FGR
2011
IEEE
268views Biometrics» more  FGR 2011»
12 years 11 months ago
Emotion recognition using PHOG and LPQ features
— We propose a method for automatic emotion recognition as part of the FERA 2011 competition [1] . The system extracts pyramid of histogram of gradients (PHOG) and local phase qu...
Abhinav Dhall, Akshay Asthana, Roland Goecke, Tom ...
ICMCS
2007
IEEE
159views Multimedia» more  ICMCS 2007»
14 years 2 months ago
Boosting Face Retrieval by using Relevant Set Correlation Clustering
We present a method to improve the performance of face retrieval in news videos by using the relevant-set correlation (RSC) clustering model. In this method, faces of a person are...
Duy-Dinh Le, Shin'ichi Satoh, Michael E. Houle
ACL
2011
12 years 11 months ago
Semi-supervised Relation Extraction with Large-scale Word Clustering
We present a simple semi-supervised relation extraction system with large-scale word clustering. We focus on systematically exploring the effectiveness of different cluster-based ...
Ang Sun, Ralph Grishman, Satoshi Sekine