Green AI-Enhanced Machine Learning Approach f...

Green AI-Enhanced Machine Learning Approach for Fruit Quality Assessment

Author Name : Dr. S. Selvi

DOI: https://doi.org/10.56025/IJARESM.2023.11623783

ABSTRACT

The demand for accurate and efficient fruit quality evaluation methods has increased in recent years. This paper proposes a machine learning-based approach for fruit quality assessment using convolutional neural networks (CNN). The proposed approach can detect fruit quality features such as ripeness, size, color, and bruises. A dataset of fruit images with different quality features has been collected. The dataset has been divided into a training set, a validation set, and a test set. The CNN model has been trained using the training set and the model gets fine-tuned using the validation set. The results show that CNNs are effective for fruit quality evaluation and can provide accurate and efficient results. The proposed approach has the potential to be used in the fruit industry for quality control and sorting applications.

Keywords: Convolution Neural Network, Fruit Quality Assessment, Image Processing, Machine Learning,