Please use this identifier to cite or link to this item:
https://rda.sliit.lk/handle/123456789/3449
Full metadata record
DC Field | Value | Language |
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dc.contributor.author | Pemasinghe, W.D.S.S | - |
dc.date.accessioned | 2023-07-28T06:19:54Z | - |
dc.date.available | 2023-07-28T06:19:54Z | - |
dc.date.issued | 2023-02 | - |
dc.identifier.uri | https://rda.sliit.lk/handle/123456789/3449 | - |
dc.description.abstract | Human-elephant conflict (HEC) has become a major concern in Sri Lanka that results in many unfortunate human and elephant deaths. Methods that are currently in place to mitigate HEC, such as electrical fences have undesirable consequences resulting in both human and elephant casualties. In this paper, we have proposed a method based on computer vision and deep learning that has promising potential for detecting and repelling elephants without endangering the lives of elephants or humans. We have used EfficientDet-Lite models that provide a good compromise between accuracy and performance to be usable with a resource-constrained device like a Raspberry Pi. | en_US |
dc.language.iso | en | en_US |
dc.subject | Development | en_US |
dc.subject | Elephant Detection | en_US |
dc.subject | Repellent System | en_US |
dc.subject | EfficientDet-Lite models | en_US |
dc.title | Development Of An Elephant Detection And Repellent System Based On EfficientDet-Lite models | en_US |
dc.type | Thesis | en_US |
Appears in Collections: | 2022 |
Files in This Item:
File | Description | Size | Format | |
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MS21901126_signed_thesis_final i.pdf | 386.17 kB | Adobe PDF | View/Open | |
MS21901126_signed_thesis_final.pdf Until 2050-12-31 | 7.86 MB | Adobe PDF | View/Open Request a copy |
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