Detection of sweetness level for fruits (watermelon) with machine learning
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...
Saved in:
Main Authors: | Wan Nazulan, Wan Nurul Suraya, Asnawi, Ani Liza, Mohd Ramli, Huda Adibah, Jusoh, Ahmad Zamani, Ibrahim, Siti Noorjannah, Mohamed Azmin, Nor Fadhillah |
---|---|
格式: | Conference or Workshop Item |
语言: | English English |
出版: |
IEEE
2020
|
主题: | |
在线阅读: | 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 |
标签: |
添加标签
没有标签, 成为第一个标记此记录!
|
相似书籍
-
Stress Classification based on Speech Analysis of MFCC Feature via Machine Learning
由: Hilmy, Muhammad Syazani Hafiy, et al.
出版: (2021) -
Machine learning approach for stress detection based on alpha-beta and theta-beta ratios of EEG signals
由: Altaf, Hunain, et al.
出版: (2021) -
Boosting of fruit choices using machine learning‑based pomological recommendation system
由: Dutta, Monica, et al.
出版: (2023) -
The needs of collaborative tool for practicing pair
programming in educational setting
由: Asnawi, Ani Liza, et al.
出版: (2019) -
Comparison of X-band satellite link measurements with radar derived rain attenuation in the tropics
由: Badron, Khairayu, et al.
出版: (2014)