Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/2150
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dc.contributor.authorAbeywardhana, D. L-
dc.contributor.authorDangalle, C. D-
dc.contributor.authorNugaliyadde, A-
dc.contributor.authorMallawarachchi, Y-
dc.date.accessioned2022-05-02T10:51:09Z-
dc.date.available2022-05-02T10:51:09Z-
dc.date.issued2022-01-09-
dc.identifier.citationAbeywardhana, D.L., Dangalle, C.D., Nugaliyadde, A. et al. An ultra-specific image dataset for automated insect identification. Multimed Tools Appl 81, 3223–3251 (2022). https://doi.org/10.1007/s11042-021-11693-3en_US
dc.identifier.urihttp://rda.sliit.lk/handle/123456789/2150-
dc.description.abstractAutomated identifcation of insects is a tough task where many challenges like data limitation, imbalanced data count, and background noise needs to be overcome for better performance. This paper describes such an image dataset which consists of a limited, imbalanced number of images regarding six genera of subfamily Cicindelinae (tiger beetles) of order Coleoptera. The diversity of image collection is at a high level as the images were taken from diferent sources, angles and on diferent scales. Thus, the salient regions of the images have a large variation. Therefore, one of the main intentions in this process was to get an idea about the image dataset while comparing diferent unique patterns and features in images. The dataset was evaluated on diferent classifcation algorithms including deep learning models based on diferent approaches to provide a benchmark. The dynamic nature of the dataset poses a challenge to the image classifcation algorithms. However transfer learning models using softmax classifer performed well on the current dataset. The tiger beetle classifcation can be challenging even to a trained human eye, therefore, this dataset opens a new avenue for the classifcation algorithms to develop, to identify features which human eyes have not identifed.en_US
dc.language.isoenen_US
dc.publisherSpringer USen_US
dc.relation.ispartofseriesMultimedia Tools and Applications;Pages 1-29-
dc.subjectAutomated insect identifcationen_US
dc.subjectLimited dataen_US
dc.subjectTiger beetlesen_US
dc.subjectInter-class similarityen_US
dc.titleAn ultra-specific image dataset for automated insect identificationen_US
dc.typeArticleen_US
dc.identifier.doi10.1007/s11042-021-11693-3en_US
Appears in Collections:Department of Information Technology
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Research Papers - Open Access Research
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Research Publications -Dept of Information Technology

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