Anomaly detection in image streams with explainable AI
dc.contributor.author | Wijesinghe, N | |
dc.contributor.author | Perera, R | |
dc.contributor.author | Sellahewa, N | |
dc.contributor.author | Talagala, P | |
dc.date.accessioned | 2023-12-29T04:57:37Z | |
dc.date.available | 2023-12-29T04:57:37Z | |
dc.date.issued | 2023 | |
dc.description.abstract | We 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.doi | https://doi.org/10.31705/BPRM.v3(2).2023.5 | en_US |
dc.identifier.issn | 2815-0082 | en_US |
dc.identifier.issue | 2 | en_US |
dc.identifier.journal | Bolgoda Plains Research Magazine | en_US |
dc.identifier.pgnos | pp. 23-27 | en_US |
dc.identifier.uri | http://dl.lib.uom.lk/handle/123/21995 | |
dc.identifier.volume | 3 | en_US |
dc.identifier.year | 2023 | en_US |
dc.language.iso | en | en_US |
dc.publisher | University of Moratuwa | en_US |
dc.subject | novel anomaly detection framework | en_US |
dc.subject | prevent deforestation | en_US |
dc.title | Anomaly detection in image streams with explainable AI | en_US |
dc.type | Article-Full-text | en_US |
Files
Original bundle
1 - 1 of 1
Loading...
- Name:
- Article 05- Anamaly Detection in image streams with Explainable AI.pdf
- Size:
- 424.86 KB
- Format:
- Adobe Portable Document Format
- Description:
- Article 05
License bundle
1 - 1 of 1
Loading...
- Name:
- license.txt
- Size:
- 1.71 KB
- Format:
- Item-specific license agreed upon to submission
- Description: