Results 181 to 190 of about 109,015 (219)

Anomaly detection in trajectories

2016 24th Signal Processing and Communication Application Conference (SIU), 2016
In this work, we study the problem of anomaly detection of the trajectories of objects in a visual scene. For this purpose, we propose a novel representation for trajectories utilizing covariance features. Representing trajectories via co-variance features enables us to calculate the distance between the trajectories of different lengths. After setting
Hamza Ergezer, Kemal Leblebicioglu 0001
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Sparse Coding with Anomaly Detection

Journal of Signal Processing Systems, 2013
We consider the problem of simultaneous sparse coding and anomaly detection in a collection of data vectors. The majority of the data vectors are assumed to conform with a sparse representation model, whereas the anomaly is caused by an unknown subset of the data vectors - the outliers - which significantly deviate from this model.
Amir Adler, Michael Elad, Yacov Hel-Or, Ehud Rivlin   +3 more
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Anomaly detection for diagnosis

[1990] Digest of Papers. Fault-Tolerant Computing: 20th International Symposium, 2002
The author presents a method for detecting anomalous events in communication networks and other similarly characterized environments in which performance anomalies are indicative of failure. The methodology, based on automatically learning the difference between normal and abnormal behavior, has been implemented as part of an automated diagnosis system
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Detecting Anomalies in Graphs

2007 IEEE Intelligence and Security Informatics, 2007
Graph data represents relationships, connections, or affinities. Normal relationships produce repeated, and so common, substructures in graph data. We present techniques for discovering anomalous substructures in graphs, for example small cliques, nodes with unusual neighborhoods, or small unusual subgraphs, using extensions of spectral graph ...
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Detecting motion anomalies

Proceedings of the 8th ACM SIGSPATIAL Workshop on GeoStreaming, 2017
An unsupervised methodology is presented for the detection of motion anomalies using spatial context and multivariate statistical tests. The method is applied to GPS data captured for a taxi fleet in Porto, Portugal; and, AIS data captured for ships operating in the Aegean Sea.
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Detecting Anomalies and Intruders

2006
Brittleness is a well-known problem in expert systems where a conclusion can be made, which human common sense would recognise as impossible e.g. that a male is pregnant. We have extended previous work on prudent expert systems to enable an expert system to recognise when a case is outside its range of experience.
Akara Prayote, Paul Compton
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Anomaly detection through registration

Pattern Recognition, 1999
Abstract We introduce a system that automatically segments and classifies features in brain MRI volumes. It segments 144 structures of a 256×256×124 voxel image in 18 minutes on an SGI computer with four 194 MHz R10K processors. The algorithm uses an atlas, a hand-segmented and classified MRI of a normal brain, which is warped in 3-D using a ...
Mei Chen, Takeo Kanade, Henry A. Rowley, Dean Pomerleau   +3 more
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Anomalous Anomaly Detection

2022 IEEE International Conference On Artificial Intelligence Testing (AITest), 2022
Muyeed Ahmed, Iulian Neamtiu
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Anomaly detection for internetworms

2005 9th IFIP/IEEE International Symposium on Integrated Network Management, 2005. IM 2005., 2005
Internet worms have become a major threat to the Internet due to their ability to rapidly compromise large numbers of computers. In response to this threat, there is a growing demand for effective techniques to detect the presence of worms and to reduce the worms' spread.
Yousof Al-Hammadi, Christopher Leckie
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Anomaly Detection Based Intrusion Detection

Third International Conference on Information Technology: New Generations (ITNG'06), 2006
This paper is devoted to the problem of neural networks as means of intrusion detection. We show that properly trained neural networks are capable of fast recognition and classification of different attacks. The advantage of the taken approach allows us to demonstrate the superiority of the neural networks over the systems that were created by the ...
Dima Novikov, Roman V. Yampolskiy, Leon Reznik   +2 more
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