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Issue Date
2020-01-07Keywords
Dryers (equipment)Neural networks
Development and testing
K-means
Leaf classification
Tea processing
Tea
Metadata
Show full item recordPublisher
Institute of Physics PublishingJournal
Journal of Physics: Conference SeriesDOI
10.1088/1742-6596/1432/1/012075Additional Links
https://iopscience.iop.org/article/10.1088/1742-6596/1432/1/012075Abstract
The process of classification of the raw material, is one of the most important procedures in any tea dryer, being responsible for ensuring a good quality of the final product. Currently, this process in most tea processing companies is usually handled by an expert, who performs the work manually and at his own discretion, which has a number of associated drawbacks. In this work, a solution is proposed that includes the planting, design, development and testing of a prototype that is able to correctly classify photographs corresponding to samples of raw material arrived at a dryer, using intelligence techniques (IA) type supervised for Classification by Artificial Neural Networks and not supervised with K-means Grouping for class preparation. The prototype performed well and is a reliable tool for classifying the raw material slammed into tea dryers.Type
info:eu-repo/semantics/articleRights
info:eu-repo/semantics/openAccessAttribution-NonCommercial-ShareAlike 4.0 International
Language
engISSN
17426588EISSN
17426596ae974a485f413a2113503eed53cd6c53
10.1088/1742-6596/1432/1/012075
Scopus Count
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The following license files are associated with this item:
- Creative Commons