Cocopal -一个基于深度学习的智能系统,用于认证和标准化椰子产品的质量

K.H.R. Gunawardana, M.P.N. Deshan, M.G.S.P. Hemachandra, D. Ganegoda, N.M. Hettiarachchi, L. Weerasinghe
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引用次数: 0

摘要

目前,在斯里兰卡,以椰子为基础的产品的质量认证和标准化程序是手工完成的。这是一项费时费力的任务,由专家进行。在大多数情况下,质量仅由买家和供应商目测决定,没有科学依据。该论文报告了引入现代技术解决方案的能力,如人工智能(AI)、机器学习(ML)、图像处理(IP)和分散存储,以帮助原材料质量的认证和标准化。结果表明,所提出的系统的准确度在86%到90%的范围内,表明该技术可以改进并用作人工技术的替代方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cocopal - A Deep Learning Based Intelligent System to Certify and Standardize the Quality of Coconut Based Products
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.
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