文章基本信息

标题：Classification Quality of Tobacco Leaves as Cigarette Raw Material Based on Artificial Neural Networks
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作者：Yuslena Sari ; Ricardus Anggi Pramunendar
期刊名称：International Journal of Computer Trends and Technology
电子版ISSN：2231-2803
出版年度：2017
卷号：50
期号：3
页码：147-150
DOI：10.14445/22312803/IJCTT-V50P126
出版社：Seventh Sense Research Group
摘要：Determination of the current tobacco grade classification performed by the tobacco commonly called grader with a variety of human frailties. Therefore it is necessary to develop classification automation tools. But earlier experiments need to be done first, in this case using Backpropagation Neural Network classification approach.From this research was obtained increased accuracy for the classification grade tobacco leaf with Backpropagation Neural Network method obtained an accuracy of 77.50%. This indicates that the feature extraction parameters such as shape, color, and texture applied to a Neural Network Backpropagation method can produce a level of accuracy that is quite accurate. Tests were also carried out to produce a level of precision and recall satisfactory as well. Based on the data testing eksperimet of 40 tested for classification grade tobacco leaf there are 8 different datasets that result accuracy between Backpropagation Neural Network with a grader.
关键词：image processing; classification; tobacco; back propagation neural network.