Please use this identifier to cite or link to this item:
https://rda.sliit.lk/handle/123456789/2910
Title: | Deep Learning-Based Surveillance System for Coconut Disease and Pest Infestation Identification |
Authors: | Vidhanaarachchi, S. P. Akalanka, P. K. G. C. Gunasekara, R. P. T. I. Rajapaksha, H. M. U.D Aratchige, N. S. Lunugalage, D Wijekoon, J. L |
Keywords: | Surveillance System Coconut Disease Pest Infestation Identification Deep Learning Learning-Based |
Issue Date: | 7-Dec-2021 |
Publisher: | IEEE |
Citation: | S. P. Vidhanaarachchi et al., "Deep Learning-Based Surveillance System for Coconut Disease and Pest Infestation Identification," TENCON 2021 - 2021 IEEE Region 10 Conference (TENCON), 2021, pp. 405-410, doi: 10.1109/TENCON54134.2021.9707404. |
Series/Report no.: | TENCON 2021 - 2021 IEEE Region 10 Conference (TENCON); |
Abstract: | The coconut industry which contributes 0.8% to the national GDP is severely affected by diseases and pests. Weligama coconut leaf wilt disease and coconut caterpillar infestation are the most devastating; hence early detection is essential to facilitate control measures. Management strategies must reach approximately 1.1 million coconut growers with a wide range of demographics. This paper reports a smart solution that assists the stakeholders by detecting and classifying the disease, infestation, and deficiency for the sustainable development of the coconut industry. It leads to the early detections and makes stakeholders aware about the dispersions to take necessary control measures to save the coconut lands from the devastation. The results obtained from the proposed method for the identifications of disease, pest, deficiency, and degree of diseased conditions are in the range of 88% - 97% based on the performance evaluations. |
URI: | http://rda.sliit.lk/handle/123456789/2910 |
ISSN: | 2159-3450 |
Appears in Collections: | Department of Computer systems Engineering-Scopes Research Papers - Dept of Computer Systems Engineering Research Papers - IEEE Research Papers - SLIIT Staff Publications |
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Deep_Learning-Based_Surveillance_System_for_Coconut_Disease_and_Pest_Infestation_Identification.pdf Until 2050-12-31 | 694.87 kB | Adobe PDF | View/Open Request a copy |
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