Machine Vision Based Papaya Maturity Recognition

Papaya is one of the most familiar foods around the world that is considered a vegetable as well as a fruit, based on its maturity level. It contains a strong set of health beneficiary ingredients that can prevent malicious diseases. The harvesting of Papaya first began in Southern Mexico and Costa Rica which makes it a tropical fruit. It is full of excellent nutritional and therapeutic appraisal due to its abundant origin of vitamins A and C. It's very much sensitive to frost, strong winds, and water stagnation and consequently, it rots very fast. In this project, we built a comparative neural network architecture that can detect the maturity of papaya. In our proposed architecture, the CNN model performs best than the other models. Therefore, we developed a sequential model along with four other models named as AlexNet, LeeNet, VggNet, and ResNet. Furthermore, we demonstrated the performance of each model to draw a comparison to show which one provides the best result among them. Our proposed model in this paper has 99.33% accuracy.