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» High-Level Feature Extraction Experiments for TRECVID 2007
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NIPS
2004
14 years 11 months ago
Semi-Markov Conditional Random Fields for Information Extraction
We describe semi-Markov conditional random fields (semi-CRFs), a conditionally trained version of semi-Markov chains. Intuitively, a semiCRF on an input sequence x outputs a "...
Sunita Sarawagi, William W. Cohen
DATESO
2007
104views Database» more  DATESO 2007»
14 years 11 months ago
Shape Extraction Framework for Similarity Search in Image Databases
The task of similarity search in image databases has been studied for decades, while there have been many feature extraction techniques proposed. Among the mass of low-level techni...
Jan Klima, Tomás Skopal
CVPR
2007
IEEE
15 years 11 months ago
Facial Expression Biometrics Using Tracker Displacement Features
In this paper we investigate a possibility of using the face expression information for person biometrics. The idea of this research is that person's emotional face expressio...
Sergey Tulyakov, Thomas E. Slowe, Zhi Zhang, Venu ...
87
Voted
PR
2007
165views more  PR 2007»
14 years 9 months ago
A trainable feature extractor for handwritten digit recognition
This article focusses on the problems of feature extraction and the recognition of handwritten digits. A trainable feature extractor based on the LeNet5 convolutional neural netwo...
Fabien Lauer, Ching Y. Suen, Gérard Bloch
73
Voted
SMC
2007
IEEE
133views Control Systems» more  SMC 2007»
15 years 3 months ago
Text classification using multi-word features
—We carried out a series of experiments on text classification using multi-word features. An automated method was proposed to extract the multi-words from text data set and two d...
Wen Zhang, Taketoshi Yoshida, Xijin Tang