Neural networks for tea leaf classification
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 an...
- Autores:
-
Silva, Jesús
H, H
Niebles Núñez, William
Ruiz-Lazaro, Alex
Varela, Noel
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2020
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/6236
- Acceso en línea:
- https://hdl.handle.net/11323/6236
https://repositorio.cuc.edu.co/
- Palabra clave:
- Raw material
Intelligence techniques (IA)
Neural networks
Tea leaf
- Rights
- openAccess
- License
- CC0 1.0 Universal
Summary: | 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. |
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