Mobile-Based Deep Learning Approach for Multi-Object Aiwen Mango Grade Classification
In this paper, a mobile-based deep learning approach for multi-object Aiwen mango grade classification, MDLMAGC, was proposed to instantly identify the quality grade of Aiwen mangoes through smart mobile devices. The new Ivan mango training set images could be uploaded to the cloud database for model training to improve model accuracy. Through MDLMAGC proposed in this paper, the labor cost of manual identification could be reduced. The grade of Ivan mango could be classified accurately. The different grades of Aiwen mangoes thus could adopt corresponding sales strategies to achieve the most effective sales benefits.
Authors
- Shyh-Wei Chen (ORCID: https://orcid.org/0000-0003-2540-7168)
- Hung-Wei Hsu
- Yi-Chao Wu (ORCID: https://orcid.org/0000-0001-9628-4308)
Institutions
- National Taipei University of Technology (TW)
- Tunghai University (TW)
- National Kaohsiung University of Science and Technology (TW)
Publication Details
- Journal
- Electronics
- Published
- 2025-08-11
- DOI
- https://doi.org/10.3390/electronics14163188
- Citations
- 1
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 1.75
Funders
- National Science and Technology Council