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» On the use of spiking neural network for EEG classification
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HIS
2004
13 years 10 months ago
K-Ranked Covariance Based Missing Values Estimation for Microarray Data Classification
Microarray data often contains multiple missing genetic expression values that degrade the performance of statistical and machine learning algorithms. This paper presents a K rank...
Muhammad Shoaib B. Sehgal, Iqbal Gondal, Laurence ...
JUCS
2008
136views more  JUCS 2008»
13 years 8 months ago
Crime Scene Representation (2D, 3D, Stereoscopic Projection) and Classification
: In this paper we provide a study about crime scenes and its features used in criminal investigations. We argue that the crime scene provides a large set of features that can be u...
Ricardo O. Abu Hana, Cinthia Obladen de Almendra F...
ICDAR
2009
IEEE
13 years 6 months ago
Invariant Primitives for Handwritten Arabic Script: A Contrastive Study of Four Feature Sets
The choice of relevant features is very decisive in handwriting recognition rate. Our aim is to present some useful structural and statistical features and see their degree of var...
Sofiene Haboubi, Samia Maddouri, Noureddine Ellouz...
ICANN
2005
Springer
14 years 2 months ago
Self Organizing Map (SOM) Approach for Classification of Power Quality Events
In this work, Self Organizing Map (SOM) is used in order to classify the types of defections in electrical systems, known as Power Quality (PQ) events. The features for classificat...
Emin Germen, Dogãn Gökhan Ece, Öm...
NIPS
1997
13 years 10 months ago
Computing with Action Potentials
Most computational engineering based loosely on biology uses continuous variables to represent neural activity. Yet most neurons communicate with action potentials. The engineerin...
John J. Hopfield, Carlos D. Brody, Sam T. Roweis