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» Neural Meshes: Statistical Learning Based on Normals
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ICC
2007
IEEE
128views Communications» more  ICC 2007»
14 years 9 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
15 years 9 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...
86
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GECCO
2008
Springer
261views Optimization» more  GECCO 2008»
14 years 10 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
15 years 3 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
14 years 11 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...