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» Learning Classifiers from Semantically Heterogeneous Data
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ECCV
2006
Springer
13 years 11 months ago
Recognition and Segmentation of 3-D Human Action Using HMM and Multi-class AdaBoost
Our goal is to automatically segment and recognize basic human actions, such as stand, walk and wave hands, from a sequence of joint positions or pose angles. Such recognition is d...
Fengjun Lv, Ramakant Nevatia
LREC
2010
126views Education» more  LREC 2010»
13 years 11 months ago
Predictive Features for Detecting Indefinite Polar Sentences
In recent years, text classification in sentiment analysis has mostly focused on two types of classification, the distinction between objective and subjective text, i.e. subjectiv...
Michael Wiegand, Dietrich Klakow
IFIP12
2008
13 years 11 months ago
P-Prism: A Computationally Efficient Approach to Scaling up Classification Rule Induction
Top Down Induction of Decision Trees (TDIDT) is the most commonly used method of constructing a model from a dataset in the form of classification rules to classify previously unse...
Frederic T. Stahl, Max A. Bramer, Mo Adda
MM
2006
ACM
175views Multimedia» more  MM 2006»
14 years 3 months ago
The challenge problem for automated detection of 101 semantic concepts in multimedia
We introduce the challenge problem for generic video indexing to gain insight in intermediate steps that affect performance of multimedia analysis methods, while at the same time...
Cees Snoek, Marcel Worring, Jan van Gemert, Jan-Ma...
BMCBI
2006
99views more  BMCBI 2006»
13 years 9 months ago
Genetic algorithm learning as a robust approach to RNA editing site prediction
Background: RNA editing is one of several post-transcriptional modifications that may contribute to organismal complexity in the face of limited gene complement in a genome. One f...
James Thompson, Shuba Gopal