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of 24
pro vyhledávání: '"Calikus Ece"'
Autor:
Christodoulou Vasiliki, Saprikis Vaggelis, Kythreotou Louiza, Christodoulos Monogios, Calikus Ece, Joselowitz Jared
Publikováno v:
E3S Web of Conferences, Vol 436, p 06009 (2023)
Climate change is a substantial threat. Awareness-raising and education are key goals. Social media provide an opportune context for the delivery of science education content. However, little research has examined which video features elicit engageme
Externí odkaz:
https://doaj.org/article/19c7f75473064adeb14d4e69bb1c949c
Deep learning-based methods have achieved a breakthrough in image anomaly detection, but their complexity introduces a considerable challenge to understanding why an instance is predicted to be anomalous. We introduce a novel explanation method that
Externí odkaz:
http://arxiv.org/abs/2402.14469
Publikováno v:
Data Mining Knowledge Discovery (2022)
In contextual anomaly detection, an object is only considered anomalous within a specific context. Most existing methods for CAD use a single context based on a set of user-specified contextual features. However, identifying the right context can be
Externí odkaz:
http://arxiv.org/abs/2101.11560
In recent years, there has been increased research interest in detecting anomalies in temporal streaming data. A variety of algorithms have been developed in the data mining community, which can be divided into two categories (i.e., general and ad ho
Externí odkaz:
http://arxiv.org/abs/1909.06927
Publikováno v:
Applied Energy, 252, p.113409 (2019)
Understanding the heat usage of customers is crucial for effective district heating operations and management. Unfortunately, existing knowledge about customers and their heat load behaviors is quite scarce. Most previous studies are limited to small
Externí odkaz:
http://arxiv.org/abs/1901.04863
Publikováno v:
In Expert Systems With Applications 1 October 2020 155
Publikováno v:
In Energy Procedia September 2018 149:345-353
Publikováno v:
International Journal of Data Science and Analytics; 20240101, Issue: Preprints p1-15, 15p
Akademický článek
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Autor:
Calikus, Ece
Anomaly detection is the problem of identifying data points or patterns that do not conform to normal behavior. Anomalies in data often correspond to important and actionable information such as frauds in financial applications, faults in production
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______681::953dcd851a7dd0c662655e71794336bc
http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-46404
http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-46404