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TIP
2008
169views more  TIP 2008»
13 years 8 months ago
Weakly Supervised Learning of a Classifier for Unusual Event Detection
In this paper, we present an automatic classification framework combining appearance based features and Hidden Markov Models (HMM) to detect unusual events in image sequences. One...
Mark Jager, Christian Knoll, Fred A. Hamprecht
ISDA
2010
IEEE
13 years 6 months ago
Detecting anomalies in spatiotemporal data using genetic algorithms with fuzzy community membership
A genetic algorithm is combined with two variants of the modularity (Q) network analysis metric to examine a substantial amount fisheries catch data. The data set produces one of t...
Garnett Carl Wilson, Simon Harding, Orland Hoeber,...
SCN
2008
Springer
136views Communications» more  SCN 2008»
13 years 8 months ago
An efficient data structure for network anomaly detection
Abstract-- Despite the rapid advance in networking technologies, detection of network anomalies at high-speed switches/routers is still far from maturity. To push the frontier, two...
Jieyan Fan, Dapeng Wu, Kejie Lu, Antonio Nucci
TJS
2010
182views more  TJS 2010»
13 years 6 months ago
A novel unsupervised classification approach for network anomaly detection by k-Means clustering and ID3 decision tree learning
This paper presents a novel host-based combinatorial method based on k-Means clustering and ID3 decision tree learning algorithms for unsupervised classification of anomalous and ...
Yasser Yasami, Saadat Pour Mozaffari
DCOSS
2007
Springer
14 years 2 months ago
Separating the Wheat from the Chaff: Practical Anomaly Detection Schemes in Ecological Applications of Distributed Sensor Networ
Abstract. We develop a practical, distributed algorithm to detect events, identify measurement errors, and infer missing readings in ecological applications of wireless sensor netw...
Luís M. A. Bettencourt, Aric A. Hagberg, Le...