Coconut Classification Using Python with Machine Learning
This project, Coconut Classification Using Machine Learning in Python, focuses on automating the classification of coconuts based on their visual features. By leveraging computer vision and machine learning techniques, the system aims differentiate coconuts based ripeness, quality and other key attributes. implementation training machine learning models, including K-Nearest Neighbors (KNN), Convolutional Neural Net (CNN), Logistic Regression, using image datasets of coconuts. Data augmentation techniques are applied to improve model accuracy and generalization. The project’s goal is to provide an efficient and reliable solution for industries such as agriculture and food processing, reducing manual labor and enhancing quality control. user-friendly interface is also integrated to enable easy classification for end users.
Authors
- Gina Kusuma (ORCID: https://orcid.org/0000-0003-0728-5144)
Institutions
- PES University (IN)
Publication Details
- Journal
- International Journal of Scientific Research in Computer Science Engineering and Information Technology
- Published
- 2025-07-30
- DOI
- https://doi.org/10.32628/cseit25111397
- Primary Topic
- Coconut Research and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00