Reference | Title | Fruit(s) | Algorithm(s) | Accuracy(ies) |
Dubey, and Jalal [11] | A robust approach for fruit and vegetable classification | Plum, potato, cashew, onion, orange, kiwi, apple, watermelon, pear and peach | SVM | 99% |
Savakar [10] | Identification and classification of bulk fruits images | Apple, mango, sweet lemon and orange | ANN | 94% |
Khaing, Naung, and Htut [14] | Control system for fruit classification | Apples, bananas, blueberries, kiwi fruits, raspberries | CNN | 94% |
Nosseir and Ahmed [17] | Automatic classification for fruits’ types and identification of rotten ones | Banana, apple, and strawberry | K-NN, Linear SVM and Quadratic SVM | 95%, 96% and 98% |
Zeeshan, Prabhu, Arun and Rani [19] | Fruit classification system | Apple, Grapes, Bosch Pears, Banana, Blackberries, Blueberries, Anjou Pears, Cantaloupes, etc. | SVM | 87 % |
Ummapure and Hanchinal [18] | Multi features based fruit classification | Apple, Banana, Cherry, Grapes, and Mango | SVM, MLP and RF | 99.98% |
Our Proposed Method | Application of machine learning techniques for Okra shelf life prediction | Okra fruits only | SVM, Naïve Bayes and Decision Tree | 100% |
Logistic Regression | 88.89% | |||
K-NN | 83.33% |