Anomaly detection in image streams with explainable AI

dc.contributor.authorWijesinghe, N
dc.contributor.authorPerera, R
dc.contributor.authorSellahewa, N
dc.contributor.authorTalagala, P
dc.date.accessioned2023-12-29T04:57:37Z
dc.date.available2023-12-29T04:57:37Z
dc.date.issued2023
dc.description.abstractWe define an anomaly as an unlikely occurrence that deviates from a typical behavior [1]. An anomaly could be a defect in a production line, sudden stock market fluctuations or natural disasters such as deforestation, volcanic eruptions, or floods [2] [3]. The assistance of an intelligent system to identify such disturbances would be very beneficial to initiate methods to prevent such situations in the early stages. This study forwards an AI based anomaly detection system and its testing stages primarily focused on the detection of deforestation, where when deforestation occurs, it shows an anomalous scenario which deviates from the typical sights of lush green forests.en_US
dc.identifier.doihttps://doi.org/10.31705/BPRM.v3(2).2023.5en_US
dc.identifier.issn2815-0082en_US
dc.identifier.issue2en_US
dc.identifier.journalBolgoda Plains Research Magazineen_US
dc.identifier.pgnospp. 23-27en_US
dc.identifier.urihttp://dl.lib.uom.lk/handle/123/21995
dc.identifier.volume3en_US
dc.identifier.year2023en_US
dc.language.isoenen_US
dc.publisherUniversity of Moratuwaen_US
dc.subjectnovel anomaly detection frameworken_US
dc.subjectprevent deforestationen_US
dc.titleAnomaly detection in image streams with explainable AIen_US
dc.typeArticle-Full-texten_US

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