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ICPR
2006
IEEE
16 years 5 months ago
Enhancing Training Set for Face Detection
We present a novel method to enhance training set for face detection with nonlinearly generated examples from the original data. The motivation is from Support Vector Machines (SV...
Ruiping Wang, Jie Chen, Shiguang Shan, Wen Gao
IJAR
2011
118views more  IJAR 2011»
14 years 7 months ago
A sequential pattern mining algorithm using rough set theory
Sequential pattern mining is a crucial but challenging task in many applications, e.g., analyzing the behaviors of data in transactions and discovering frequent patterns in time se...
Ken Kaneiwa, Yasuo Kudo
SP
2008
IEEE
159views Security Privacy» more  SP 2008»
15 years 4 months ago
Inferring neuronal network connectivity from spike data: A temporal data mining approach
Abstract. Understanding the functioning of a neural system in terms of its underlying circuitry is an important problem in neuroscience. Recent developments in electrophysiology an...
Debprakash Patnaik, P. S. Sastry, K. P. Unnikrishn...
135
Voted
MM
2005
ACM
172views Multimedia» more  MM 2005»
15 years 10 months ago
Learning the semantics of multimedia queries and concepts from a small number of examples
In this paper we unify two supposedly distinct tasks in multimedia retrieval. One task involves answering queries with a few examples. The other involves learning models for seman...
Apostol Natsev, Milind R. Naphade, Jelena Tesic
ACL
1997
15 years 5 months ago
Learning Features that Predict Cue Usage
Our goal is to identify the features that predict the occurrence and placement of discourse cues in tutorial explanations in order to aid in the automatic generation of explanatio...
Barbara Di Eugenio, Johanna D. Moore, Massimo Paol...