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» Neural Meshes: Statistical Learning Based on Normals
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ICC
2007
IEEE
128views Communications» more  ICC 2007»
13 years 7 months ago
The Power of Temporal Pattern Processing in Anomaly Intrusion Detection
Abstract— A clear deficiency in most of todays Anomaly Intrusion Detection Systems (AIDS) is their inability to distinguish between a new form of legitimate normal behavior and ...
Mohammad Al-Subaie, Mohammad Zulkernine
ICIAP
2005
ACM
14 years 7 months ago
A Neural Adaptive Algorithm for Feature Selection and Classification of High Dimensionality Data
In this paper, we propose a novel method which involves neural adaptive techniques for identifying salient features and for classifying high dimensionality data. In particular a ne...
Elisabetta Binaghi, Ignazio Gallo, Mirco Boschetti...
GECCO
2008
Springer
261views Optimization» more  GECCO 2008»
13 years 8 months ago
SSNNS -: a suite of tools to explore spiking neural networks
We are interested in engineering smart machines that enable backtracking of emergent behaviors. Our SSNNS simulator consists of hand-picked tools to explore spiking neural network...
Heike Sichtig, J. David Schaffer, Craig B. Laramee
ICANN
2007
Springer
14 years 1 months ago
Some Properties of the Gaussian Kernel for One Class Learning
This paper proposes a novel approach for directly tuning the gaussian kernel matrix for one class learning. The popular gaussian kernel includes a free parameter, σ, that requires...
Paul F. Evangelista, Mark J. Embrechts, Boleslaw K...
DAGM
2008
Springer
13 years 9 months ago
Segmentation of SBFSEM Volume Data of Neural Tissue by Hierarchical Classification
Three-dimensional electron-microscopic image stacks with almost isotropic resolution allow, for the first time, to determine the complete connection matrix of parts of the brain. I...
Björn Andres, Ullrich Köthe, Moritz Helm...