Image Classification of Mangoes Using CNN VGG16 and AlexNet
DOI:
https://doi.org/10.57185/joss.v2i8.103Abstract
Mango is one of the fruits that is often consumed by Indonesian people and is the fruit with the third largest amount of production in Indonesia, but currently, there are obstacles in the export of mangoes in Indonesia where fruit conditions and regulations weaken the mango export process in Indonesia. This study focuses on comparisons and classifications in the use of the CNN VGG16 and AlexNet architectures for classifying arum manis mango images. In this research, 4 images of Arum Manis mangoes will be used with a dataset of 400. With the results of the classification carried out with the two architectural models, CNN VGG16 provides a high accuracy of 92.50% with the use of epoch 50 while the use of AlexNet gets an accuracy of 79.64%. This research was conducted to provide a solution to overcome the quality of mangoes that are not in accordance with the production standards of mangoes to be exported.
Published
Issue
Section
License
Copyright (c) 2023 Aldo Leviko Marshal, Ahmad Nurul Fajar
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-ShareAlike 4.0 International. that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
