Classification of Starfruit Ripeness using Neural Network Technique
Starfruit is one of tropical food has been exported by Malaysia country to Europe, Middle East and Canada. The demand for this fruit is high. The exported fruits have been graded by FAMA. The graded system for starfruit ripeness is manually done by a human. The human cannot cope with high demand gra...
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Ahmad K.A.; Abdullah N.; Osman M.K.; Sulaiman S.N.; Abdullah M.F.; Hussain Z. |
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Ahmad K.A.; Abdullah N.; Osman M.K.; Sulaiman S.N.; Abdullah M.F.; Hussain Z. 2-s2.0-85093840271 Classification of Starfruit Ripeness using Neural Network Technique 2020 Proceedings - 10th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2020 10.1109/ICCSCE50387.2020.9204929 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85093840271&doi=10.1109%2fICCSCE50387.2020.9204929&partnerID=40&md5=913ad7d91ae474e5c28d79cc787e75b4 Starfruit is one of tropical food has been exported by Malaysia country to Europe, Middle East and Canada. The demand for this fruit is high. The exported fruits have been graded by FAMA. The graded system for starfruit ripeness is manually done by a human. The human cannot cope with high demand graded the ripeness of starfruit. This paper proposed a classification of starfruit ripeness system using artificial neural network. The methodology of image processing has successfully demonstrated. The segmentation technique using a Euclidean distance metric has been demonstrated. The classification using a sigmoid activation function in ANN improved the recognition system. The classification system has an accuracy of 97.33%. The system can recognize the unripe, ripe and overripe of starfruit. © 2020 IEEE. Institute of Electrical and Electronics Engineers Inc. English Conference paper |
| author |
2-s2.0-85093840271 |
| spellingShingle |
2-s2.0-85093840271 Classification of Starfruit Ripeness using Neural Network Technique |
| author_facet |
2-s2.0-85093840271 |
| author_sort |
2-s2.0-85093840271 |
| title |
Classification of Starfruit Ripeness using Neural Network Technique |
| title_short |
Classification of Starfruit Ripeness using Neural Network Technique |
| title_full |
Classification of Starfruit Ripeness using Neural Network Technique |
| title_fullStr |
Classification of Starfruit Ripeness using Neural Network Technique |
| title_full_unstemmed |
Classification of Starfruit Ripeness using Neural Network Technique |
| title_sort |
Classification of Starfruit Ripeness using Neural Network Technique |
| publishDate |
2020 |
| container_title |
Proceedings - 10th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2020 |
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| container_issue |
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| doi_str_mv |
10.1109/ICCSCE50387.2020.9204929 |
| url |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85093840271&doi=10.1109%2fICCSCE50387.2020.9204929&partnerID=40&md5=913ad7d91ae474e5c28d79cc787e75b4 |
| description |
Starfruit is one of tropical food has been exported by Malaysia country to Europe, Middle East and Canada. The demand for this fruit is high. The exported fruits have been graded by FAMA. The graded system for starfruit ripeness is manually done by a human. The human cannot cope with high demand graded the ripeness of starfruit. This paper proposed a classification of starfruit ripeness system using artificial neural network. The methodology of image processing has successfully demonstrated. The segmentation technique using a Euclidean distance metric has been demonstrated. The classification using a sigmoid activation function in ANN improved the recognition system. The classification system has an accuracy of 97.33%. The system can recognize the unripe, ripe and overripe of starfruit. © 2020 IEEE. |
| publisher |
Institute of Electrical and Electronics Engineers Inc. |
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| language |
English |
| format |
Conference paper |
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scopus |
| collection |
Scopus |
| _version_ |
1828987872267468800 |