Kurum Yazarı "Öǧrenci, Arif Selçuk" WoS İndeksli Yayınlar Koleksiyonu İçin Listeleme
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Anomaly Detection in Walking Trajectory
Öğrenci, Arif Selçuk (IEEE, 2018)Analysis of the walking trajectory and the detection of anomalies in this trajectory, provide important benefits in the fields of health and security. In this work, two methods to detect anomalies in trajectories, are ... -
A Hybrid Deep Learning Framework for Unsupervised Anomaly Detection in Multivariate Spatio-Temporal Data
Karadayı, Yıldız; Aydın, Mehmet Nafiz; Öğrenci, Arif Selçuk (Mdpi, 2020)Multivariate time-series data with a contextual spatial attribute have extensive use for finding anomalous patterns in a wide variety of application domains such as earth science, hurricane tracking, fraud, and disease ... -
Mathematical models for phase transitions in biogels
Bilge, Ayşe Hümeyra; Öğrenci, Arif Selçuk; Pekcan, Önder (World Scientific Publ Co Pte Ltd, 2019)It has been shown that reversible and irreversible phase transitions of biogels can be represented by epidemic models. The irreversible chemical sol-gel transitions are modeled by the Susceptible-Exposed-Infected-Removed ... -
Unsupervised Anomaly Detection in Multivariate Spatio-Temporal Data Using Deep Learning: Early Detection of COVID-19 Outbreak in Italy
Karadayı, Yıldız; Aydın, Mehmet Nafiz; Öğrenci, Arif Selçuk (Ieee-Inst Electrıcal Electronıcs Engıneers Inc, 2020)Unsupervised anomaly detection for spatio-temporal data has extensive use in a wide variety of applications such as earth science, traffic monitoring, fraud and disease outbreak detection. Most real-world time series data ...