Anomaly detection in sliding windows using dissimilarity metrics in time series data

Erkuş, Ekin Can
Purutçuoğlu Gazi, Vilda
4th International Conference on Arti ficial Intelligence and Applied Mathematics in Engineering (ICAIAME 2022)


Anomaly Detection and Activity Perception Using Covariance Descriptor for Trajectories
Ergezer, Hamza; Leblebicioğlu, Mehmet Kemal (2016-10-16)
In this work, we study the problems of anomaly detection and activity perception through the trajectories of objects in crowded scenes. For this purpose, we propose a novel representation for trajectories via covariance features. Representing trajectories via feature covariance matrices enables us to calculate the distance between the trajectories of different lengths. After setting this proposed representation and calculation of distances between trajectories, anomaly detection is achieved by sparse repres...
Anomaly detection using sparse features and spatio-temporal hidden markov model for pedestrian zone video surveillance
Gündüz, Ayşe Elvan; Taşkaya Temizel, Tuğba; Temizel, Alptekin; Department of Information Systems (2014)
Automated analysis of crowd behavior for anomaly detection has become an important issue to ensure the safety and security of the public spaces. Public spaces have varying people density and as such, algorithms are required to work robustly in low to high density crowds. Mainly, there are two different approaches for analyzing the crowd behavior: methods based on object tracking where individuals in a crowd are tracked and holistic methods where the crowd is analyzed as a whole. In this work, the aim is to ...
Anomaly Based Target Detection in Hyperspectral Images via Graph Cuts
Bati, Emrecan; Erdinc, Acar; Cesmeci, Davut; Caliskan, Akin; Koz, Alper; AKSOY, SELİM; Erturk, Sarp; Alatan, Abdullah Aydın (2015-05-19)
The studies on hyperspectral target detection until now, has been treated in two approaches. Anomaly detection can be considered as the first approach, which analyses the hyperspectral image with respect to the difference between target and the rest of the hyperspectral image. The second approach compares the previously obtained spectral signature of the target with the pixels of the hyperspectral image in order to localize the target. A distinctive disadvantage of the aforementioned approaches is to treat ...
Anomaly detection from personal usage patterns in web applications
Vural, Gürkan; Yöndem (Turhan), Meltem; Department of Computer Engineering (2006)
The anomaly detection task is to recognize the presence of an unusual (and potentially hazardous) state within the behaviors or activities of a computer user, system, or network with respect to some model of normal behavior which may be either hard-coded or learned from observation. An anomaly detection agent faces many learning problems including learning from streams of temporal data, learning from instances of a single class, and adaptation to a dynamically changing concept. The domain is complicated by ...
Fault detection in combinational circuits by neural networks
Arslan, Mesut Murat; Halıcı, Uğur; Department of Electrical and Electronics Engineering (1994)
Citation Formats
E. C. Erkuş and V. Purutçuoğlu Gazi, “Anomaly detection in sliding windows using dissimilarity metrics in time series data,” presented at the 4th International Conference on Arti ficial Intelligence and Applied Mathematics in Engineering (ICAIAME 2022), Baku, Azerbaycan, 2022, Accessed: 00, 2022. [Online]. Available: