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79
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CORR
2006
Springer
93views Education» more  CORR 2006»
14 years 11 months ago
Functional dissipation microarrays for classification
In this article, we describe a new method of extracting information from signals, called functional dissipation, that proves to be very effective for enhancing classification of h...
D. Napoletani, Daniele C. Struppa, T. Sauer, V. Mo...
71
Voted
ICPR
2006
IEEE
16 years 25 days ago
Fast Linear Feature Detection Using Multiple Directional Non-Maximum Suppression
Linear feature detection is a very important issue in the areas of image analysis, computer vision, and pattern recognition. It has found applications in many diverse areas such a...
Changming Sun, Pascal Vallotton
89
Voted
AI
2006
Springer
15 years 3 months ago
Language Patterns in the Learning of Strategies from Negotiation Texts
The paper shows how to construct language patterns that signal influence strategies and tactical moves corresponding to such strategies. We apply corpus analysis methods to the ext...
Marina Sokolova, Stan Szpakowicz
NIPS
1994
15 years 1 months ago
Efficient Methods for Dealing with Missing Data in Supervised Learning
We present efficient algorithms for dealing with the problem of missing inputs (incomplete feature vectors) during training and recall. Our approach is based on the approximation ...
Volker Tresp, Ralph Neuneier, Subutai Ahmad
ACII
2005
Springer
15 years 5 months ago
Physiological Sensing and Feature Extraction for Emotion Recognition by Exploiting Acupuncture Spots
Previous emotion recognition systems have mainly focused on pattern classification, rather than utilizing sensing technologies or feature extraction methods. This paper introduces ...
Ahyoung Choi, Woontack Woo