Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/3353
Title: Cocopal - A Deep Learning Based Intelligent System to Certify and Standardize the Quality of Coconut Based Products
Authors: Gunawardana, K.H.R.
Deshan, M.P.N.
Hemachandra, M.G.S.P.
Ganegoda, D
Hettiarachchi, N. M
Weerasinghe, L
Keywords: Cocopal
Deep Learning
Intelligent System
Certify
Standardize
Quality
Coconut Based Products
Issue Date: 9-Dec-2022
Publisher: IEEE
Citation: K. H. R. Gunawardana, M. P. N. Deshan, M. G. S. P. Hemachandra, D. Ganegoda, N. M. Hettiarachchi and L. Weerasinghe, "Cocopal - A Deep Learning Based Intelligent System to Certify and Standardize the Quality of Coconut Based Products," 2022 4th International Conference on Advancements in Computing (ICAC), Colombo, Sri Lanka, 2022, pp. 470-475, doi: 10.1109/ICAC57685.2022.10025099.
Series/Report no.: 2022 4th International Conference on Advancements in Computing (ICAC);
Abstract: The procedure of certifying and standardizing the quality of the coconut-based products is done manually in Sri Lanka at precent. It is a time consuming and labor-intensive task and is conducted by experts. In most cases, the quality is decided solely by visual inspections by buyers and suppliers, with no scientific basis. The paper reports the capacity of bringing modern technology solutions such as Artificial Intelligence (AI), Machine Learning (ML), Image Processing (IP), and decentralized storage to aid in the certification and standardization of the quality of raw materials.Results showed that the accuracy of the proposed system is in the 86% to 90% range and showed that this technique could beimproved and used as an alternative to manual techniques.
URI: https://rda.sliit.lk/handle/123456789/3353
ISBN: 979-8-3503-9809-0
Appears in Collections:4th International Conference on Advancements in Computing (ICAC) | 2022
Department of Computer Science and Software Engineering
Research Papers - Dept of Computer Science and Software Engineering
Research Papers - IEEE
Research Papers - SLIIT Staff Publications



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