Identification and classification of Green Leafy Vegetables using CNN models

Identifying and classifying vegetables in big farms is a challenge, especially when the vegetables are similar in colour and shape. Manual identification of vegetables takes time and is prone to errors. Therefore, the automatic classification process of the precision farming, increasingly using image processing and pattern recognition to identify fruits and vegetable, is becoming essential to identify and classify vegetables in big farms. In this paper, an automatic system for the identification and classification of green leafy vegetables, similar in colour and shape was evaluataed using five different deep learning models such as CNN, MobileNet, VGG-16, Inception V3 and ResNet 50. The accuracies of these models achieved in this paper vary from 67% to 99%. The model with the highest accuracy is the MobileNet.