Detection of sweetness level for fruits (watermelon) with machine learning

• Main Authors: Wan Nazulan, Wan Nurul Suraya, Asnawi, Ani Liza, Mohd Ramli, Huda Adibah, Jusoh, Ahmad Zamani, Ibrahim, Siti Noorjannah, Mohamed Azmin, Nor Fadhillah
• Format: Conference or Workshop Item
• Language: English; English
• Published: IEEE 2020
• Subjects: T10.5 Communication of technical information; TK7885 Computer engineering
• Online Access: http://irep.iium.edu.my/86522/7/86522_Detection%20of%20Sweetness%20Level%20for%20Fruits%20_new.pdf; http://irep.iium.edu.my/86522/13/86522_Detection%20of%20Sweetness%20Level%20for%20Fruits_scopus.pdf; http://irep.iium.edu.my/86522/; https://ieeexplore.ieee.org/document/9289712

The inspection and grading of the watermelon are done manually but it is a tedious job and it is difficult for the graders to maintain constant vigilance. Thus, the image processing has widely been used for identification, detection, grading and quality evaluation in the agricultural field. The...