Publicação
Almond variety detection using deep learning
| Resumo: | Quality is the major factor for modern industries because the high-quality of products is the basis for success in today’s highly competitive market, so improving the product quality is not a choice is paramount to any business to be even competitive. This thesis aims to solve one of the many problems that exist in today’s market, with regard to the quality and how to evaluate the quality before putting the product in the market. We have implemented a Deep-learning based technique that helps classify/identify almonds based only on their visual features, this can help in many ways from which we can mention: supply chain optimization, Sorting food, and matching customer taste . . . . In the conclusion of this thesis, we propose many features that can be developed that can be added to our model, from scaling it to other products, to deploying it, in order to reach the full potential of our solution. |
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| Autores principais: | Benarous, Ahmed Omar Farouq |
| Assunto: | Deep learning Computer vision Food quality |
| Ano: | 2020 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Instituto Politécnico de Bragança |
| Idioma: | inglês |
| Origem: | Biblioteca Digital do IPB |
| Resumo: | Quality is the major factor for modern industries because the high-quality of products is the basis for success in today’s highly competitive market, so improving the product quality is not a choice is paramount to any business to be even competitive. This thesis aims to solve one of the many problems that exist in today’s market, with regard to the quality and how to evaluate the quality before putting the product in the market. We have implemented a Deep-learning based technique that helps classify/identify almonds based only on their visual features, this can help in many ways from which we can mention: supply chain optimization, Sorting food, and matching customer taste . . . . In the conclusion of this thesis, we propose many features that can be developed that can be added to our model, from scaling it to other products, to deploying it, in order to reach the full potential of our solution. |
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