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138
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ICPR
2010
IEEE
15 years 8 months ago
Learning an Efficient and Robust Graph Matching Procedure for Specific Object Recognition
We present a fast and robust graph matching approach for 2D specific object recognition in images. From a small number of training images, a model graph of the object to learn is a...
Jerome Revaud, Guillaume Lavoue, Yasuo Ariki, Atil...
140
Voted
BIBE
2009
IEEE
131views Bioinformatics» more  BIBE 2009»
15 years 7 months ago
Learning Scaling Coefficient in Possibilistic Latent Variable Algorithm from Complex Diagnosis Data
—The Possibilistic Latent Variable (PLV) clustering algorithm is a powerful tool for the analysis of complex datasets due to its robustness toward data distributions of different...
Zong-Xian Yin
111
Voted
ESANN
2000
15 years 5 months ago
Discriminative learning for neural decision feedback equalizers
In this work new Decision-Feedback (DF) Neural Equalizers (DFNE) are introduced and compared with classical DF equalizers and Viterbi demodulators. It is shown that the choice of ...
Elio D. Di Claudio, Raffaele Parisi, Gianni Orland...
122
Voted
CORR
2007
Springer
112views Education» more  CORR 2007»
15 years 3 months ago
Learning from compressed observations
— The problem of statistical learning is to construct a predictor of a random variable Y as a function of a related random variable X on the basis of an i.i.d. training sample fr...
Maxim Raginsky
153
Voted
IJON
2011
90views more  IJON 2011»
14 years 7 months ago
Fault tolerant machine learning for nanoscale cognitive radio
We introduce a machine learning based classifier that identifies free radio channels for cognitive radio. The architecture is designed for nanoscale implementation, under nanosc...
Joni Pajarinen, Jaakko Peltonen, Mikko A. Uusitalo